{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:22:28.610288Z",
     "start_time": "2018-02-18T14:22:28.550731Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "import sys\n",
    "sys.path.insert(0, '../src/easyesn/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:22:29.494574Z",
     "start_time": "2018-02-18T14:22:28.825415Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using Numpy backend.\n"
     ]
    }
   ],
   "source": [
    "from easyesn import PredictionESN, BaseESN\n",
    "from easyesn import helper as hlp\n",
    "from easyesn.optimizers import GradientOptimizer\n",
    "import matplotlib.pyplot as plt\n",
    "import easyesn\n",
    "\n",
    "np.random.seed(42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:24:29.636138Z",
     "start_time": "2018-02-18T14:24:29.595588Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#generate train/test data\n",
    "\n",
    "\n",
    "inputLength = 1000\n",
    "trainingLength = int(inputLength*0.7)\n",
    "data = np.linspace(0, 10*np.pi, inputLength).reshape(-1,1)\n",
    "\n",
    "\"\"\"\n",
    "inputData = np.sin(data)\n",
    "outputData = np.cos(data)\n",
    "\n",
    "\"\"\"\n",
    "inputData = np.loadtxt(\"MackeyGlass_t17.dat\").reshape((-1, 1))\n",
    "outputData = inputData[84:]\n",
    "inputData = inputData[:-84]\n",
    "\n",
    "\n",
    "inputLength = len(inputData)\n",
    "trainingLength = int(inputLength*0.7)\n",
    "\n",
    "inputDataTraining = inputData[:trainingLength]\n",
    "inputDataValidation = inputData[trainingLength:]\n",
    "\n",
    "outputDataTraining = outputData[:trainingLength]\n",
    "outputDataValidation = outputData[trainingLength:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:24:15.882882Z",
     "start_time": "2018-02-18T14:24:15.638597Z"
    },
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "class EnsembleESN(object):\n",
    "    def __init__(self, n_input, n_output, ensembleMembers, judgeESN):\n",
    "        self.n_input = n_input\n",
    "        self.n_output = n_output\n",
    "        \n",
    "        self._ensemble = []\n",
    "        if type(ensembleMembers) is tuple:\n",
    "            #first item of tuple is number of members\n",
    "            #second item is the funtion to generate the member\n",
    "            \n",
    "            for i in range(ensembleMembers[0]):\n",
    "                self._ensemble.append(ensembleMembers[1](i))\n",
    "        else:\n",
    "            for item in ensembleMembers:\n",
    "                self._ensemble.append(item)\n",
    "                \n",
    "        #check the validity of the ensemble members\n",
    "        for esn in self._ensemble:\n",
    "            if not issubclass(type(esn), easyesn.BaseESN.BaseESN):\n",
    "                raise ValueError(\"All objects inserted in/generated by ensembleMembers argument must be inherited from BaseESN\")\n",
    "            else:\n",
    "                if esn.n_input != n_input or esn.n_output != n_output:\n",
    "                    raise ValueError(\"At least one member of the ensemble has different input/output dimensions as the entire ensemble is ought to have\")\n",
    "             \n",
    "        self._judgeESN = judgeESN\n",
    "        if judgeESN.n_input != n_input + len(self._ensemble) or esn.n_output != n_output:\n",
    "                raise ValueError(\"The judge ESN has to have n_input = {0} and n_output = {1} for this ensemble\".format(n_input + len(self._ensemble), n_output))\n",
    "            \n",
    "   \n",
    "    def fit(self, inputData, outputData, transientTime=\"AutoReduce\", transientTimeCalculationEpsilon = 1e-3, transientTimeCalculationLength = 20, verbose=0):\n",
    "        trainErrors = []\n",
    "        trainPredictions = []\n",
    "        \n",
    "        #TODO: get value for transientTimeValue\n",
    "        transientTimeValue = 100\n",
    "        \n",
    "        #reshape the input/output data to have the shape (timeseries, time, dimension)\n",
    "        if len(outputData.shape) <= 2:\n",
    "            outputData = outputData.reshape((1, -1, self.n_output))\n",
    "        if len(inputData.shape) <= 2:\n",
    "            inputData = inputData.reshape((1, -1, self.n_input))\n",
    "\n",
    "        if inputData is not None:\n",
    "            inputData = np.array(inputData)\n",
    "        if outputData is not None:\n",
    "            outputData = np.array(outputData)\n",
    "        \n",
    "        #only use the FIRST timeseries submitted\n",
    "        inputData = inputData[0]\n",
    "        outputData = outputData[0]\n",
    "        \n",
    "        #train ensemble\n",
    "        for esn in self._ensemble:\n",
    "            error = esn.fit(inputData, outputData)\n",
    "            esn.resetState()\n",
    "            prediction = esn.predict(inputData)\n",
    "            trainPredictions.append(prediction)\n",
    "            trainErrors.append(error)\n",
    "            \n",
    "            \n",
    "        judgeESNTrainData = np.array(trainPredictions)#.reshape(-1, len(trainPredictions))\n",
    "        judgeESNTrainData = np.vstack((inputData.reshape((1, -1, 1)), judgeESNTrainData))\n",
    "        judgeESNTrainData = judgeESNTrainData.T[0, transientTimeValue:]\n",
    "        \n",
    "        #judgeESNTrainData = np.array(trainPredictions).reshape(-1, len(trainPredictions))\n",
    "        #judgeESNTrainData = np.hstack((inputData.reshape((-1, self.n_input)), judgeESNTrainData))\n",
    "        #judgeESNTrainData = judgeESNTrainData[transientTimeValue:]\n",
    "  \n",
    "        trainErrors = np.array(trainErrors)  \n",
    "        weights = trainErrors / np.sum(trainErrors) * len(self._ensemble)\n",
    "\n",
    "        #set input weights\n",
    "        self._judgeESN._expandedInputScaling = np.vstack((np.repeat(1.0, 1 + self.n_input).reshape(-1, 1), weights.reshape(-1, 1))).flatten()\n",
    "        \n",
    "        judgeError = self._judgeESN.fit(judgeESNTrainData, outputData[transientTimeValue:, :], transientTime=\"Auto\")\n",
    "        \n",
    "        return judgeError\n",
    "\n",
    "    def predict(self, inputData, continuation=True, initialData=None, update_processor=lambda x:x, verbose=0):\n",
    "        #get predictions\n",
    "        predictions = []\n",
    "        for esn in self._ensemble:\n",
    "            prediction = esn.predict(inputData)\n",
    "            predictions.append(prediction)\n",
    "                    \n",
    "        judgeESNInputData = np.array(predictions)\n",
    "        judgeESNInputData = np.vstack((inputData.reshape(1, -1, self.n_input), judgeESNInputData))\n",
    "        judgeESNInputData = judgeESNInputData.T[0]\n",
    "\n",
    "        finalPrediction = self._judgeESN.predict(judgeESNInputData)\n",
    "        \n",
    "        return finalPrediction, predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:35:46.564772Z",
     "start_time": "2018-02-18T14:35:34.254065Z"
    }
   },
   "outputs": [],
   "source": [
    "def generateEnsembleMember(id):\n",
    "    return PredictionESN(n_input=1, n_output=1, n_reservoir=1000, leakingRate=0.2, spectralRadius=1.25, regressionParameters=[1e-2], solver=\"lsqr\", feedback=False)\n",
    "\n",
    "judge = PredictionESN(n_input=10+1, n_output=1, n_reservoir=50, leakingRate=0.2, regressionParameters=[1e-2], solver=\"lsqr\", feedback=False)\n",
    "ensemble = EnsembleESN(1, 1, (10, generateEnsembleMember), judge)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:37:30.352689Z",
     "start_time": "2018-02-18T14:35:46.566775Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.03956900467381278\n"
     ]
    }
   ],
   "source": [
    "print(ensemble.fit(inputDataTraining, outputDataTraining))\n",
    "finalPrediction, singlePredictions = ensemble.predict(inputDataValidation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:37:30.673507Z",
     "start_time": "2018-02-18T14:37:30.354192Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAD8CAYAAACfF6SlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzsvXu0bVlZH/ibc629z71VPAoERMAI\niDhE2mhA045od1Q0JCbqaDWtaY0xRNse7ehOR9Mttg98xRjadxvEoEJEXoIgKvIQbBCBEopnQRVQ\nVVQV9b51q+7jPPZeaz76j/m95tprPw733HOLW3uOcce5Z5+112vO+c3f9/t+3zddzhnbtm3btm3b\n9uBq/lLfwLZt27Zt27Ydf9sa/23btm3btgdh2xr/bdu2bdu2B2HbGv9t27Zt27YHYdsa/23btm3b\ntgdh2xr/bdu2bdu2B2HbGv9t27Zt27YHYdsa/23btm3btgdh2xr/bdu2bdu2B2FrL/UNLGuPetSj\n8hOf+MRLfRvbtm3btm2fVe2aa665N+f86HXHPWCN/xOf+ES8733vu9S3sW3btm3b9lnVnHO3bHLc\nlvbZtm3btm17ELat8d+2bdu2bXsQtq3x37Zt27ZtexC2rfHftm3btm17ELat8d+2bdu2bXsQtq3x\n37Zt27ZtexC2rfHftm3btm17ELat8X8gtDOfvtR3sG3bdvTtlncDd374Ut/Fti1pW+N/qdt1fwr8\n2tOBG992qe/kgdf27wPu/tilvoujabe8G/jEmy/NtefnL811f//ZwAu/9tJc+6hatwe88nuBM7de\n6js58rY1/pe63f7+8vO2B2g28+4p4K/+A9DtH/+1f+8fAS/46uO/7sVov/9s4GXfefzX/cirgV98\nAnDPdcd/7cuhXf8G4LrXA2/5qUt9J0fetsb/UrfYlZ/tzqW9j2Xt3b8JvP2XgE++6fivfe8nys8Y\njve6KQHn7z7ea16s9tHXlp+nrr+097Gm5ZyRcz7Wa+7OA2La8Jru8jOVl98Tfba1RIbNP0DLLJ27\no/yM/aW7hzA73utd8/vALz/18kDLzaT8PO4F9JDtSc99A378tdce2/Vyznj6T78J//6PPrT6wAf6\n/LyAtjX+h2k5A2/7eeDeG47wnKn8dM3RnXOD9tE7zuIrfvbNeP+t968+kO8P7qLf09KWjtlwfeod\n5ec9l0G8gdG0f+BP9Zf/7fHx6oEQ/x9/4PbVB26N/2Xe7vwQ8Naf04myrO2fBt7xfOAl//Torp1i\n+emP1/i/4SN34v79Hu/85L0rj0uMGN2lNP7xeK8nC/JlMD3YeB33sxyCwgkxrT/oiFu/6TW3xv8y\nby/+Z8Bf/z9AvyaoyfTDUaonMhm2Y+Y7Gfm0zWqjfuMdZXG468zuRb+npe24kf8l8sYuSuOF87gX\n0EPQhN2lMP5hw/nGz7E1/pdp48k+O7v6uJ6M/1EOBJmcx2vgPCH5tCbgdX7/AABwMD9Czv9tPw9c\n92ebH3/JjP9FmB7HvMgruDhmA3uIOE0Xjt/4b7zghIsw5x8gbWv8AZ0Y69BKKIbwSAcCX/uYDVxD\nxn/tHCDjkY4y4PuO5wOv/J82P/5SGf+LYTCPG4FfInBxGOM/f0Ab/3n5ucGcP+giXvqeW9YCqgdK\n2xp/AJEN27oJ0pPxb6brT3rP9cDr/tf1KguZnMerpmk8Gf81SNSTAUzxmI2WbcdsuHYPaMKzDPdC\nmx0Dx9zP8u42eIezPuLU+fn6c775J4GP/8XqY3iubNCOGvlfc8v9uOaW1UKGftNrhs2f4xfe8DH8\nxOuuxTtvWB1He6C0rfEHkHlyrkNl/SGQ/2ueA3zwpcCpNXJBdss3kOLtzQPed/N966+9QWN9c0yr\nJ4EHG/9LKBU8ZrT8ibsK/df1R2T8rQE55oUsHwL5//DLPoCv/IW/XKm3zzkD7/oN4OXftfpkh0L+\nR9u/3/6Cd+HbX/Culcf0MeFL3C2YYM17YeS/waJ997ly7H53CYHSIdrW+ANo3YbUCw/oZgPjz3zx\nOvS4qdcB4Of+7GP4jt9+N249feHZtrGf4XntizGZr45zNEdt/NcsNuPfOV6DuTcrfRa6DVDw7dcA\n1/7x6vPtGYHAUdFnpz4OPO/hwB0fWHnYjXdT/26wgP7ldSWxbXe+/H2f2d/w/q3xX9Pnl4L2Sfff\ngr/YeS5+sv2D1Qfyc2wwBlU6saV9PvvaprSPnxzdNXlx2ABZXHfnOQDA6b0NjNKa9tRTb8G/at+M\n/+7Tv7XyOEH+R4W+PxMq5SiN/x0fUDS3pHmavP0myP+/fD3w6u9feciZc0YpdVTPwrTLR1698rCz\n+8V45UNcN8Tlxuvs3oaIvrfHrTaGlyLgm/cLLfQM/4nVB8r8XP/+lOpfI4s+dwdw36fWnu9it63x\nNy2EdQHfQ0T+ebCsAwF8zg2Ci3wqdwSa+0Acvl+z6LDxzxsg1lPn53jXOr5zUzrALjZHZTDv/BDw\nO/8QuOYlKw9j478R8t+gdZ155iNC/tffXRaU/W71+RqU9xjXjW3TVmng+37D/rNU15qxfSmQP19y\n7Uzi/trA801El60tU/ErXwL8xpevPd/Fbpe38c8ZuPmdG8vrum4N0hPkv4H+e0M65677CprfxPhv\nytNv0ljnv84lV9pnPfL/3t+9Gv/iRVevTNrJa1C33qClDdZf++qbTuPme/dWH3TuzvLzk6urazau\nXK/vj8ZQd/PNUfCm7T03ngYAnJ+tfjfcf4cx/quUMP38M0D+a/rvUiD/sCGNyQAgbrBo85zqt2qf\nB0D75FuAF38zcPVvb3T42gDfoZD/Zsb/ztNnyn82WKB4THWbJqisaIzkg1v9LI0g/w0C0qduwTf4\na3DmYPlE2dvfMF7RHy5I+j/+znvw7F9/x5qj6L2t0e9PCC33R6Rw6i2oOCr6jN5JwGog0lL/hbC5\n99SvoH3ipsg/mkX+GJH/ppm7sS/3F9aYwJvuLvTQrafXAAso4j8KcHYc7fLLXLBtlyoz3vHBjQ5f\ny/EeRu3DxjKvnuw7IEO5Ce1DgyusG1zz3eKdTE6uuD8Kaq4xHsr5rzceL2+fhye4e3FX+NGlx+zu\n7eIha8+EQxl/fi+zfvV7SSnBA8hutbvfkgIkH8ZQ57y0BEaFljfo51kf4Z3DtF1umKaeFqg1U1ho\nnw0W7yswwyPduZUGNG5KhVmkvOaZjxL5H/QRX+puxhQ9YsoiaR62ROMrrhn/kT3VQ3jmq2ImD6R2\neSN/Rnob1s1Zi24vAvKfHsL4M6e4Ft384uOBX1/DKdLk3NR4bGIIn+AK3x8Olpe/2N0U+YfNqZKD\nPuJKHOBhWI3OPnxb8bJOnV+9yE/kmQ9hlFa8n9BvjoIB4IU/8xz8xq/8zMpjpkRNzdPqKSy0zwYU\n1nPbl+GdO/8WoVuubd8c+R/C+B9hDsmsj/jznR/Ha3d+euU8yfQc/Rrj7+g5GrfeoIeUcRXOK6X6\nAG+Xt/E/ZNG0tXJGQaMbdK5w/keH/A9F++zetfLPmRansMb4t7kc5zZSO1Di2IqNXzbmjMPmaHl3\nFnDNzg/hwyd+YOVxN9xVjP9et/r9sfb7UAqnFR5eCmax2YDe+9/b1+JH939t5TG8QM3z6v7bcaX/\n4gbP8r3tX5Zj56uM/6bI3z7zGtqHPLZ1OoZ7zs3wJx9cXYVz1um1VsUuEgXhQ15Dm2X24NfPz3+w\n/1Z88MT/jIeeWV4N9rj3LFjVLnPjv74in03FXlvCYEMXMKWMnifJmkk3PcTkzCni6e6mlbTPxqnl\ntNCt4/yVAlk/+L1jt3f5QpFWoMr6/jY3HufnASfcemTbMqJfY2XY+OfDlHdYsTjmQzzLpq2hRXkd\nbTGlZ4mHQNchLPeMNkX+h3lmNtKTNWWnf/HFr8FXvvZrcN+dy2WSB70+5yo6KRO4WB8z2QzEAcDT\n5mW/4kfe/5Glx1wKZdOydpkbf0b+yw2cRQfrjT8ZrjWD+a3X34Mkxn81YmbknzcIVH1X98f4s52f\nwENPXbP0mPMrEnRsc4T8+zXIZ8LIP28eMFylLEmbqn0OQRvszja7twm/63XHuc1onwrFrTAO7iIY\nf5/ZO1k3vsq1D7OQhRWxr7Qh8v/U3Wf0lzVod94nvHL6s3hu+9KVx/23p/8Yj3P3ofvony49xhr/\nVUCIVWfrjH8j73n9+xMKaYUd2Rr/42pSy3x5B/cmtTytC9T0m2ny7zhzgB23WU2VKTabxADwlHgj\nAGCyt5zSOT/bTNLHXOY6N5SR/2GMVuxXIP+Njf/mVMmqjFTb2IVnemrpcRt6O9VEXtV/F8H4uw0L\nAk4P4bnJuVd5bhsi//l88zhHFxP+vr8e3+9MpdfQAT//ucCHXqEf0Wn6FSB8Zv64sm7Vhsafac9N\n+s2xIGOFWZ2vmBvH3S5v45/Xc/6d4TfXcryM/A+jW16r9uno2htMThqA2WpV7roW+NifyK+bGkKf\nynXXIXpG/ocxHqtoA2wcMNzcYG76zIzA1zFjO7zgrennc2ah7VdIKXPY/Fk25YR93iAQn7MICg7T\nf2lFFnbesN5Ra2vmfCZSz9nZEvd504/raUTtZt7RPdcB732R/GqR/0rVDdE+ac2eDYz8N3p/9Jxx\nBbiYr0nKO852JMbfOfds59zHnXM3OOd+bOTv/8459zHn3Iedc291zn3BUVx3bdugLnswAci1iUw8\niTfkMOmky28vBlERbBRcZB1xNs/zuh8CXvUv5dfzG1IgnNnrVg3qnD8z5L/CEG6K/A+jkNmU9uHA\na1qT18lUXFqzcNt3PV8hgTwM7bNKY2+bxwYF25KOr0N5HCtoi037TxAzsBYAjRd24yRE/Rv3WvWO\nfv+fAH/+I4LkZ6aoWtoI+a9RuzH4WfMM5SCSRa8wqxZsHkpNdhHaBRt/51wD4LcA/GMATwPw3c65\npw0O+wCAZ+acvwzAqwH8pwu97kZNtiBcYfyNMmUt+pZSDKsnaCUxWzE5bYzhMMiiuvpdH6nuaVND\n2Ig7u9p4cKmDdRPYtlXZkHlDzviO0+fMl+p387efug8fv0vlpEuR//m7Ss6D3BhN+Lxi2OcsCpm1\ngeZ9BQ7dKnf+MLLHDbOKBZGuAizGUK8zXjYrO68o+ZE3LM9ReZSfic4/LvaB45pL9vCO+pd217PI\nP65w8Ry9m1WGGgAafhebeGRjyH92Frjzw/Lr3ILN497bYdCOAvl/FYAbcs435Zw7AK8A8K32gJzz\nX+Wc2cq+B8ATjuC6a9uZ3TIwbr1vufTQcphrOyOOI//zsx6fvFuNkY0jbKr/3mQgsNs7OqZpspw7\nWDI5r30NcPY2+bUR2mfFxPwMueq0Kpt0Q+SYViD/f/7Cd+Mf/Zpm8y41/r/8xcCLnmWuzch/xbA3\nz7xuQd7b17yCtCLI7dIhZI+zJWP19vcDnV6vTRss3uZZ1gGbino5gv47DNU1SvtwhnClzBopn8BG\nmUBWFfA1BvtF77gB//bl7zfnL/PEYU15k0NIPRX5m3t++XcDL/xasQO98RDX1hK7yO0ojP/jAXza\n/H4bfbasPQfA6E4QzrkfdM69zzn3vlOnTl3wjd13thj/6+9YXgM/zXWyrU1kWlKE7ef/7Dp846++\nQ4xQruqarKJA9G+bIf8Vxp+Mwf6Y8U8RePW/LhUoqTWb6PfD4ZKThvcyfs7NkGOlOFmHwFd5O2Y/\nBS5psaqXLbJd1yf7e8b4rwz4bo78+zH6qNsH/svXAa/6PvmoYQnihsj/MGWVVyL/Tauyrnjm33zr\nJ/HGa++U37uxCC5/nzj5lLIW3KsOz9XxB51F/nrUv3nbM/Dsj/2f8run5/BrPKLmEAFfsR/22NtJ\nmXdQ1E+9KfJ3mHpLF6MdhfEfI1BHfSTn3PcAeCaA54/9Pef8OznnZ+acn/noRz/6gm+MO86vMOqx\nQv7raJ9x5P86Sjy5f4/+bhDaqkETg0X+mxhXon3GXFAe/AcjOnqeSFzuAsb4r0I+ZgKv9BAGbdUi\n6jbcGSkuQY6zEUOxu+H+wo7R5Ko8id5SJWvoipk+y6o4x2GQfzcfMf583ze+VT5S5L/CeFkvZs11\nq/dqF7I3/wTwe8/W3zdVa6Xlxv+X3/IJ/NBLFYWPImC+dxJrnDX1opI93wD5V2qfgXz62c17hd7y\n9E490sog+2eC/CtAxQFlphxN/4ZLuTsejqa2z20APt/8/gQAdwwPcs49C8D/DeC/zzkfTa3cdY2M\nV+tWZF/2Vu2zKedfH8eboTMCdcG47isGjUX+m9A+bIDdGKfObu+Y8R8guRCTyB7dSuPxmSH/qkzG\nzX9TFsOnflO5Hr3vlN1K5LEs4DuWtWnjHCkm+Gb8zC6tR3H9/EDEf+uQvy2DsIrqcodA/mFMDRUX\nDZAg0lXJZSkoMjsM7WPv912/ObiXzwT5q3HtQtlB6+n+UwC+udza6DPTdch4Xn/XeXmWem+C2vjv\nGyAwNqe6mNA2Xox/g4SUgWaJBuAwUs+cU4HCY3OK7s+WxE5HVDX2M21HgfzfC+CLnHNPcs5NAXwX\ngNfbA5xzXwHghQC+Jed8zxFcc6PGygTZqQsoA9HsfpS6C+f8uXYUa+x9v5nxt6nyC4YmJeBPfhi4\nTRO6eHxWSFJPBgCYzcYmUj3IuphE0eKPiK6omj3ni/8J8LLvlF89IX+/plZKqmgfPXZs79XK+Ivr\nPeYdrVdrVYZoDSWQZxrnSauorhUoeNhGy1/I99VCiVFaFVMyiHod8reKm1WeW0PAZp7XbGi0ZOzs\nzQP+Yue5eP7kd6SPRvdN4O8T8n/3Tacl4GvPzaidg+9274Sxci09lUaxyH9pYDglqW3lNgn4pkXk\nnwf3HM39bVpW+mK1Czb+OecA4IcBvAnAdQBelXP+qHPuZ51z30KHPR/AQwD8kXPug8651y853ZE2\nlva11tD8za+XDT0+/bfl/g/B8eYlSV58dt6701d7tq7wOuKKyXlwH/CBPwD+8NsBFOUCV9gcRXtp\nBe0zOH7eJ0w5CW1VvushOP+wocLJR2tcl187LaF9rMyPrzkzBlOURiPvnYPcq4ybnZxr4zBmC8y0\nIkPbHwr5rzCEprUiQVxFKxojtJb2sZz/euMf4Vdm0C6juvY6MzbICxx9Zh57hPxjSsb46zn4sz98\n9w3llIZWiSPjcE5US5MIGCItl4RWC/rq95dSFkPvzPvjUtq8EAVT3nuTPTIuZjsSnX/O+Q0556fm\nnL8w5/wL9NlP5ZxfT/9/Vs75c3POX07/vmX1GY+oBXbttHPzre8GAPTnCv+dD6H2OWAlxmAisbST\nXefNaR+rLKmv/e7rbymf08DsQjLGf3mA7NxY1cwR5D/ZRL9vXPx1nH9XSQUXJx0/h99wh6e8ZOHp\nY8JXuE/iDye/gI6qh/aVdpr174sGs2EaqyrLkIBb3i2/xkMgfze3yH9FnCMt72fEHrj3Bvl1HPmz\nZNkgfykIuGIhC5svOnPL+a84tg0lntUgrcygXUZ17c1tbIHQ8FhS4AD573cRzOaNVd8NJLW1AVU5\nzrxzlpW2qRy3EvmvUrulBPzuNwHvL3sAdzFJQNpSqXzuM7v7dJ824GvOf9s1wNnVReuOul3WGb5Z\nOH/tuLvPl8/e+JESlsj95kkXTRyvk8JolA1gE0aM0UhbpfP/3b8s2uDgdwAUt1yeYwWneP85U05Z\ngmG1IZz3STI/V6odqgm8JlHHiq+XcK0A0MTNjP8y5N/FhB+bvBz/oPkowu3lHVnttBi8EW66zSOe\n24deDvz+s2UT9kqptcbV950x/itQnDPvfwEt/9G/Av7fZygKrkQANWWQzefTDTKvbQ3/0eM+8WY5\nd632Wf4sExrbbpXRBJZSXRXyj6yOs0F2fuY64Ls/j9hp+JhF47/D+xtY2oc9HzOO2fifiHv0HHn5\nIrZK8DA/B3z6auCNzy2/9knKZ9v+5uWadwmM/RKRx4u+HvjVYXrUxW2XtfEf43gPiPPbn9HfzGRf\n6Rqb5J/h5GBAxgPLottVm2hYbfjwnA8BIYXmBIAyOVfW1qeBevqsSWri5xncQxcjHgIuUmcG/s3v\nBJ73cOAUbWpdBXxHJsjHXi/KpioQO/IeudRuW9E+K5D/EtTVx4ST4GQtep75CM878t4nkttg3t85\n0ibcfW35mh0PazzBptNENFuVdf+em/GpT2hlR7tP8gIVcT3Vs5mdpesb48Cb1BCVwba2TwkPdfv0\nLOYdnrkVeOX3SJ9UnPLwXd/2vhKLectPl2sY5D/63HQvEzKaHnllvfxqb2j7bgzyZ/Bjs4ZlPRkE\nfPf7iKkg/8X7mxIwqo0rjwUdSwzUTib1YKoF2Sr1Vnm+nFxGAGAeo3jmtYiCchMohmWfdZMNdi5m\nu6yNvxspwRwo++7EpPzMFdLaTDY3VAWx2keMvznWGoV7d+f4ml96G957c8k7WIZuAeBhrhjn3pPx\nt8hiDIXnWIJ2cWTSDZD/rE94uONJbM5FLuzZT7yTvrZi8N/5IeBV3wv8RdFOz2c2eL14f7zRuDcL\nyqr9E5bRBn3IQlkFytEIlatP1x5B/pO8OB5k5eYcim7Ngmda248j/yv+89/Fk172NWIcfYX8lxhM\nMjp2pyxGpPtEN/LtdH3Ew2njmupdv/G5wHV/CtxQ6vJXCqSFmFLZnhCnrgcwLFK33LOcxnIvHnl1\nBm0av7ZdZDoy1HacCf8+oH36kDD1yz3fHb9o/Hks5BHkz8bfO/Mcd3wA+A+PA65/A92DGf8Dzv+O\ne+o8pC4kKRk+lpXMW8RWApPLgfN/oLadwJujm5dMpR7EmIUNaZ8VwU8vyJ+UAYbjtUG3a246hXP3\nn8IL334T3dZyTpaRPxv/LkYx/uO0T8TuLJhArll44pD2CWI8rIqB0fvL31ty9lJYwX8z3326VBrt\nZ+pxjBn/gzkF35OhaFby5OPvpotJKlWG+QFSynWuRlxO++ysNP5kPA5BdU16feYx4HB6t1t4ljha\nxwZiXHMlPS4/WfvPBf1mB7uyk1e1KLPBbab0LMsDvrxw8laf83XIn97nJKlaq9LRv+P5wE1vl1+X\n9Z/1FpgKSRVYYuPPAd8yX1POuh/DyP3JHgwjYM7WXeK9MK5Ipe+8jV3c/E76+dd0D+NyVQB478dv\nLdcgE7rc+NN1yfi3nZa6PsweCxejXdbG/2QorrRFytxZ4qJVWZAbJswMFglHXSy8tuEkbSLHUz78\nfHz4xA/iCseDfrnxP5lq4z/rzeAaW6RSxN48aiAXQM864qHO/+CcFPxyBvlzbf9PnSqGnT2TmN0i\n8meDS8ajn9sg94jxJ8+gsQujHfwpVc+1ynhc4Yj2CT1mIeIELLLmd1R7FTFlPDyTsa4msqjH6VKb\nK2QmQZH/GBXBKLdG/quNv93shlHwXIx/af3e/fo9e4+8bwWdqwr4DsbM1Z8opT5Oz8t8WNd/XK5h\nJ43UwsoZeNvPA/9VdRw18l8EGAAQuMJlVYOo/LznTHm3Z+fl+AxTKXTkHcp7NV4E90lnvamUgTDX\nmBeyXDMTxXTveeqDFbRPmBVgyTG5LiaccCO0ojxr+dt0boz/ZVDb5wHbroyE/M3A56JLUmlx00Qm\n6qiU3cJxQ86/rQycToLHfbrwu1eh3Bdz/jG7BUNzgpBJ55TzlwVrRE2TYkBIGsgFDOc7QP5pX42H\nRf5ch5w9DM52nWO6mAk8p3c7vbJ81yD/scWJs5nbZDMczXE/+wjgFd8tv/rUq5Z8GecfAmLKUha7\nXHqR5wWKt/MoR2DAUl0D2meVwRy2SbSGcLFPZoTym9zLuFvK844g/zhAroz8ozH+1bMMjH9FKwzG\n1y13FLXbXirvOM4N1z0WsKf3Mk0j6riRrF+fet0oyHpuJrGp6+fIOVfxHV7w2Pjff0BoP2fdUnFs\nfHHwOFrPkhRA84Hxn2mspjGB6z06/bs+SZnwNG9KIcD6mpzjIcY/JJzgcWiMvxSjo/e3Y5D/lva5\nWK2f4URe3HmLg4SMZPIy1/j2a0qpWIEFpCZAs3SRYOPfmHK2Vv/NtcNZY8yDq8Nkwa28MhMHTF00\n71fTPn0ISDnL3q6AoZwWjL8OQMv588YWfA422DNMFp95RueYPqT8PKdF48bccsm5MMY/DSmQT7xR\n7yv1mIONv0nyigknaZLFEJCy7lNbrs1B7kGcY/88TrqRJC+p+MrIf4XkMaVSIC9yXSTbz2PIXzn/\nOaZ0CgNELGc+YvwzvZ9uXi9kYX/JLlls/OMi8h+Ci2koi3VPxivb6qcj/Tdn2i6v97KAYf+Zaxt5\nbOg7zIPSeIDGOTjmw3MmZbu95gj4obHeGhqX+2Q+NP6dPqtVLXWpjIVdrtbKSihMFpK8HJ2jEzVe\nEg/Uegks/2SgN+114RYgcIn29b18jf/+vfLfSncrZcJVuSMlWC2ieM0PlE0izn5ajgPIQA4m0mv9\n/4Xva96EORl6niAxuwrpJTKunsvJivFvF855ReaAXvn+7jwY47+4+HR9j5SBK6HIp+cywwPaJ9nB\nb5E/vQeWlLLBnmO6mOF4wMa/IP/mvNldbGRx4lT2SYX8VySDLTEeXVDVVQgBOWfJVgZ0wg8Th/pz\nGqBzI7TPrafLO4nL0HJKZWORV/9r4J2/CsCU+wVGSyZzkTGf9Vks7XPO1KuRhbpfRK6dPEu512BQ\nuh+lfUZUaYMxsxPL884iecIzTVgbexbm51tjeOMq45/DaP9V14k95n2q+o8PFVWM4fzFqx1B/vys\nbVqUWXf2neZceYUNkgbSU+358nFzTBY834ZUPjN3RfmuQf6V8Xc1qDjRjyB/mxS2wXauR9UuX+O/\nZ42/Qd9pwO2mIBs6VOiIBx+5iB1Nzjgw/rmf4Wn+FvzM5CUG+QfE7NCjrSZgJBQz5X1Vg0X+5tox\n4NvCm+T+gFI3iI2eG3PLuw4pZzzEjexMNjCyVhFhB3VPg39Cxp8505CbmsfcPQW89WfK/9ngmGzX\nMeTIgdRJ7jAjOkeMxwjysQbTvpuT933MPF9Z8Cztw/3aDUoGnN+t0Z6cg36++aN30TOX789zW0/4\nm/4KuPoFdLJyrPXwxsQCM1p8m6SGMBu0P//YG/T/IwHBYVYolwqOy7ZIFORPntGymNLBGfyz868s\n56Qx+LC9T8mfx8YX70BVbdIKFb/1AAAgAElEQVSSBEktHN/kvozrwbU/756/rp5vHmJFVTLtw5nW\n2SD/ndwtvR4DjmlYrNLbm6xa5vy5eaPz7xKDn1oxVsBP3b/fdtdvlL8RLduFRc7fSkh5XLbReiaL\n4Oxg1R6VR9wuX+Nv3EvLi3KHcE2bnKJuvGw7uJlU52Guckj72Iy9J58uNebb3KFHiwhfGX9G/pPM\nlJO6ldWANhQKf35+1gvXPYas532PlIArsWj8eyulS1mMf0RTGTimxJinXOqZnNaMVF6c/MxSESPI\nnwb6JM+xj+IqxxHkw83lNMoZP+FTf6SXSRExZTzWqSvNaGpYHdMaf4uWWX3CYV8xuGjqRenABFnb\nMuGbHDAjOmeM6go9J9Jp/MIe95g3/uDCsVft32yer9ybLGQUn4hEDXW5qaW6/BCin18Sp7r7o/p/\nMjw7M/WM+B5ttcuexswEPea5LDLi1Y7SPmE0ZvO40+/SS4eu1JkytF1MLNmkkstMx+WM6Yrxz2No\nWiF/KnY4s96UIv8OLTyyLDg8xzmfRmifPNHSEkC1QRB/Ou+jet30vAeVgoqAQLQUlLg58tms3yL/\nC2+MfrKr3HyRdSU1PGHM+E+KO8fGnymUgKYaCL0JYH3vzWUHyyYHdJggDYx/ZNon1pz/PE9qZGET\nTQztc4UMfh40RqkTeqSc8Sh3znx1EQV3MYnWuPc7tSGk/wrtEznO0daD3052+r+b63XHUHCKPRAL\ndXVAxl/d3kXj4bJ6ZLZf5v5KvU4stM+T3R3mM0Z7dZmEfbPxSuXtECqUBW8ZvcexDUCprhyEyx+j\n4jh936Jg612eecLXm2MJgc+1zj0bV5YJMvLn3+eY1gsUUSQcQOVicwtxqs7ubkYqnt4qiChIaeoo\nxRCAVMqCzIcL3kj/NZXnZrT9bkcvEyO6UNM+SZRKVHiN7jvljCkj/yV5LiEmPAlaIoHjKwcHA+Mv\nsaydqqQzF8LTSqj8/tp6floVEIOfvbtEhcbH2mzmHNgL7NEz0zCyeI6VLL9Y7bI3/sVlW0T+WIf8\np2z8z8lxwKJRCCNlWdvcI7gWCa4yhIkmJxc3y8uQdWVcy3V3D+YSsHSyhV8ta8sZ+DJ/k3nWxYDX\nPCTh8nu/UxlCphs5AMcTsceA9jGGnlFV051DR0idB791e4vxoOcl5JhHkA83l9PoouwGpTNSBp7o\ndJ8C3ne3H2w0zmh5jp0KDPSD/lvaJ5bqo8SjNgd0bAhHAr78nn2OZsIbQ9joQsbjaBIXOesw4Py5\n8ujc7VT9wsVN3/bR2+n6ungvHV9kgKa9LQtSvlftihVDNacAQyuOGGOfQ3mH5UHkc64NxOfsYx2z\nkcQsKaLIFIrSpcs4/y6mCggwuKgK/6UsCr/OTSlZrfyN+0CNP4//Ifgxah56tpP3f8J8Vv7+abOD\nIMdR2txhTgugBP/j1vgfactGqVJxvNRZMmlyRESDlGtDzfp1Rv5MB/S5rSbc2EYUbQ7oVyB/3lQk\nW7XP0sFFXOGeBlR50/X5rOYPU874XBgKZGTruHmIYjyCP6HF4qDBpinVSRHOf4h8jGdyZpeSfsIB\n9kDvjN5PVewt9vJcjOhVJz5G+8RR45EHC2PKGVe6WfUZsFgmmL2dbrDgMZ2hVJfxdiqDqf18dq88\nc4MenVtE9HKvQZEgAwy7EYnl5AP9fxoX1SpslITz58XbTav+4yzdG+8uY4Df1QKFNea5xU48Mn6H\ns84g8tir8Xds/GsgZZtd8Grjvy8gIeewiPxpnvG+Dzz+U854eFrM2+HmslKAwbHHwbRPnTXN/dK5\nMv7TAPnLpvc8fwb0qH1eT9doDhZjjO+/RalQtgOT3KF3yz3fLe1zBI1d4xmmFbXheHDxZE4BRUHv\nANvBE0JlYvwV+Vc0UqXmKa+zRUH+Eb4a+BGcY8BZqOMoc2jgAOBxZ3UPAjaW19xwR/WdlDOucrvY\nax5Gny2i4D5myXEIvkbBzPGfcIy27OBfNB59bsSA5aTGmq87MxLFGIPcdxBDuMj5s+rFZaXj7KJc\n0D6rs8ozn7A6/7i44AGQLOBuuODRhOcEOqFacjOePQvgYKbKl94t5/y5bIE1hFbtY2XGbOB30r7E\nOvKAAsk0vrgQWud2qnsU2o7RcjTItXoWy0WX/7vUo+NnYeQ/G2ROR110qmex9COXtEAyxl/HTptm\nAhJiTOhiwt/1N+p16FxcH4vv+8ndx+UYNsTVVp/kBe6gR+dP0keUJGd3XEtZgEFHi+dS45/tnB8f\nC7IQ0R4exUson9ndx7ivp+jRUeKmqKrM+eb94kJ6sdpla/x5U4dZrmkf7lD5LCU1/raDW+Jy2fiT\nARqiAEv7nGofC6BM9oQGGa5G/ploH6krzzRIrfbhc85zK4ZqYlQgfO8/9qq/lc9SLIN/irCALIYB\nX77+EPmzsZgO1D5Db4cn+xwTkXCmpJOdJ8q8s7SURf5NdX47+Pf3zsk5ZJGwhjUpnZBSREplws/c\nyerYOJB6Mo3Q+5P14t3Xxj8bg4nKQ9B+5udqEYTDHjX+Zp/YPrMMc/F9l/+z8T/AeTGO/Cy0wPKz\n0GKwQNux1p3RsjzLgPPn/sutzAcfO3kW9ixnhi5MMQpXrs+8nLN2OSGMBOzdACR0IeEpTnn6nAp3\nf+bcWTkPADy+v0XPwZz6Xp2YlnPGxAVE0t4z8p8P1D5RxsIJKuzGj8HGn0+pY8EviXlJwL0rxn8f\nJ+X9nTmoF6dMctVAxl8XTxPwHtul7yK1y9b4M/IrGt3FjuNATc6x0DPwtWvMA1aMP01ERsEDtAAA\n5/xV5dxIyM4vqH04YUsCvixLHCCzYCSgbHSnfTGK53GlHGvLGmQaXC2CZB0yZ2+3GwzW+Dc7o8af\nNwdPhjao3iHTOmirzVNkso/EGlIM8k6jG9A+5h3N9ksw0uUosQGbGJVjlOCpi4r854T2sgRJB8af\n3kFoTgwWb6pZI94OP3PdJ9aAsCqkzQHBDQK+9l4DB5OV9qnUXzEIyo99D4QOLQJ2Mz0Lneu6207T\nPfF+sOOeG/cF1/oXzy/XC5nlsvm+fe4F0XP/zgbInzO+ZXzFRdpnRkFOjyVCCusFxYA+JjzB3StU\nTQoBp3fneFbzATkPADwsFirrPv9Iub/9g73qvJwIFpt6Qba7e8WURUYa/A68y0uRP3uB3VD2S8/T\n50ZKovMeHjN3UpD/ebPDXE4lvmGNv1QNsNu5HuOm7g8C4z+tatZLdJ73sE0RyRHyT4voFle/AOj2\nagkgIMbfZlHKObM1/gaZEfKX+jZLMnz5nL1xNydhFwfuRHHN6bOHGK47x4AUIxqXzeSkBYsMV8i+\n7AiW1HhY488xiIbeF0+e5Jo6mUgWrYkG6FJAcOzm06SrKiwGeafRDRKeLKWyd57eZTTIv772XPIy\nCud/wnXGlWapoK3ZlGTHtriAlinQykFufmeurfrEenhJjOwi7ZNt1q8EfI0XY+m9qF5MiEFUOOdx\nBd12wPlZr/cGrkRr+89SZvQsjr0YSoYbUJV28WZNv0+9eIzy97ntv172n2VkPab2mVMF0sYseBXy\nz8kE/CO6rseO6zFrHkLPHHFw7yLK5/HXGRr3wCq4cpIMdx7/wtlXO71FGRvs+UpuAVOOEv8x4Gck\nZtKhlXvxYYY+N+idJkQGu5Naiuhp+1Qu055kcTIxia3xv/DGvN5sUJfGDTcuNxSNHaTn9k0Q8cyt\niqIGA9p2FifAOCRkeDrnCPJn459KMlj53AZe1bjyQHSxQ3BTJHhZZH7l5IvlOykFMTyMfBiFRjZ8\naBBTlszUOECOEONPyDGW7OfshgEvRj5KG+ScEAcBvs5upm04/+Tr2EBlPA4Y+SfD+dcctcgmU1jg\nefnYWO0BHKXfhwseo2Wluohnd+0gMGwpLKVXhoams8ex8YdR+1TxiyDPUtRQRFOwmiYG7M4Dppzc\nJ+WO50VD7+pArlBH7MWY4DUGiw5Qe5Y+9VLqwYnnVpcf7igAnDwt3tyfxsh1sz0ZH2NSXZeDeRdR\n4hlsEHOK6O+7VY5n48poOjqlIK9658/JcRz8r5E/3YcxrikFzXNpdiqdP6vnuDAjLwaFx18ESWV+\nMvKfFTDknNxftEqyFNH3HVqXEClPhIFTRUuN7Wp2kdrla/ypg3tXa9l5YHMHFeTflGCtrT5oO67b\nV/13rgc0u4bFBWSvIgHOI+Yh8i8/vdlLNlK8YYz2qbj22CO6Fglejn1SVFlnNpxsHNA+FgUX5N+j\nR4Psmhr5cyIKS0np/rLzS5GjqFxSlAxmMf59jRzZQOYh7WODllQgzpMKK2ZXIX+XgyBH5lF30En1\nUzH+YZxySq6tg9xcc4UVTlwUzQ0kvXRcyF6OmaBH8BwkpWc2ChlYzn9kIUMMJhCc9B7N4rjfRZHe\nSl/FriyMzlXIX2M29bMsxKkq5Vr5vLELmcRs6ncocQ82/iMxpW52YGilJcjfyF55L4YkVEhAv1fi\nW59Mj1fjSiAoOL3nR37qT815AzLRPsnXHkw/8ED5PWU/KZw/r6msxV8ImDcV598LLatjKaWI6HyZ\nn9JP1vsMQj+lpvZS5zYmt+X8L7wxP2mDYjlnNdCMNonzT65G6VVJhH7PqH14O6Ea+c8wlcxAh4zM\nVJKphcLoU2rCULA5Q9ECoIjBupUu9UiuRXJejr3WfzFu959Ht6PIMXpGjmSkSe3A+5W6zEa9GP9h\nyQs1/kUJ5Zyvs6SjJr/YZDnm8vn++vkALbOXwMZNC7nouee6yUyEK30zQP58HaSIlBJ2XEDfXKHX\ngfY/QIY76bXtROZnmULRcswO8LXCI/SK9rLERpJQWLLgdYvI30G9IisJzSZ4XZA/02zk2cSIg07L\ndHPNmUwL7XBRXjT+HKeqkX8w44v7pEkdkp9SUmT57P5zJpM1Bilxgqb2YixQit1Mje4o8o/yznKK\nEnxlNBzNZ3MD3KRkglMRxN2f93VyXuSEFENB1s0ACPR14Joza11TPGsu7JaWxEzCYPHkPi6BYFqw\nWTjiNA5QlapOESHode35K3ptS/tceMthTpNYDajdCpEXAeRIhrqWZSaiZMovihaGQSxGC3NMxWj6\nHAE6p02R50HRcnkHWnjiwOtIFlmAOc9QjL9B/lekPdzfPoZuJ4o7Ohz8PfGwExdLhnMutJRznpAP\nu71EZ3D1REb+vg74RkkeairaJ7uC1LUsgd0SMYh6JQ+Qow1yxbluT1jqmLrK+LtUaLqYXVk8WbnR\nmCBpSvjKT72gul9rPCoXnoN8slFIQCCvaCw2UEpxMDec5FnGZLVITPskjYdUexZoCYSU1DvJYhwS\n9rsoOnjORs1JRQp1zIY9klqFEwbeTgimvIFB/slPaB6UZ7n3fluETZE/Gy9JIrTxkP5AuXbjoXHz\nOZmYT5D3H7n/YpRFc+4UuJXxQMiax1zo8OH0JPp7FOMtyFpozxqEiMrKt9X4T4bOA9SrL2PGsAJk\n/Od5Iu8/p0hUr87Pr957i3zHpaDikKbODdnSPkfcUij1dZxXauOW0/vG+DPtU4xWHvDuOZrU/RSl\no4Y8JvOdczcVd7Egf6KSqoQtMv7C+ZNxta4ias6f77PJkYy/Ztu2ua+4Uqnp0nAQMgD79+GrT79G\nzh2JAilG3VcbWAuizVGMTGTkb6mZMIb8E+BK/ILvr+vqOis8+Bn5C71gSw9TApln72SQJY1caLoI\nj5x1wRMeOkUtNy3vs5PFNfvahReFk6G6Sr7GOBU3x0QMvUcSikYMXkX7aAB9geqiZ7H8txolNY7z\n2T7+Rfs2AEWOmnJ5xkSem71H7j+tW6XxiyrfhEtFG866RV+Mv1MQxMHb8ng9OtKgs/GX2I8xXqk7\nkMVjKI4o7ywiev5+FGoktTqOs5GUKvJPJTbnzFwJM6mt5FJE5jIYrdI+OWd8Y3yn3l8KYtRdM6EF\nlf4mOR+hep/RTapFlqm94CaVN5adL545ffZ9518k38k56Tjm5+cM5NlAGHFM7fI1/rEgOBjjf8/5\nmdSqF+PPtA8cYMoRwFRiRAoqIRTah1xKRtsWpYM4/4HxV0OubmWCAwbGVSRmxq1sEBBdg2QQqUOW\nSo45BUFMSXTECbhP4wLlUQJNJA/AVyVtkRQ5xpQLrQIP52uEOSZFRY6AxE7KsXv7xvjHKMZjyBlb\nnlyMPzj/wi8g/+xpsTYTKluDMjD+5ZmVUhlVOJktAhPHOSpvhxb5rLSPR1bkz/I/67YHRf5pSHWB\n0KChQGQb0EYXhBP3XivHeySElMTQwI0jfx5fqlyqs9wt8udx1xrk70aMf04BfaiNv5bSsMh/pgvh\nEs7fekuccCjIPwUx/lbNVBR0rng7Qqt0mOeJ5ujQuXKjxn+2exZf6lU9VDxQpV/sXsSq/IpIKcv7\ny772nDiob99rmVMOCUr77JFqCyh9LeOY+5cltd2W8z/SlmKZxN7rAD8/C5LM49k1zoz8XU0HpFgZ\nf812HSB/XhTcRDl/CvgOFUQ8KLRAVRLjCizSPgETMzmjoX0UeWZvastwILlVjwVmcxBAM20znKBg\n2VSEnnGCiJAyMqFvuBoth16D3PJ89B7t/e3tma0BYy9GIg9pAzP4n3DL6+gdlryBYX2kQtM1srCy\nMVVvIgJUM54pgRCjiTcMarMzz2uD3E4XFzlM9jaYFLlwLk4+JMjNC5lx26Mx/m6RAnE5aSmCFKWc\ngvRpilXBvBalhIHjWJHzgzFby5g1wD7ISmfazggKJghIblIBln9z6j+a175o/JXzN7RKfyDvbSxJ\nzyNKTCOlJOKH1BraTmpPaRKiB8fmjLcTO/RuWrxhKF2ktE9Gf77eaD2HIO/JtXWGbzK0Z5+SCCaG\ncSKOcSSv4KxQqbVncnPzd/Cxk88o8yRFjW0NqMIqsL7l/C+8pRSQ4NA0io52Z0H5UzagOSDxZB/o\nyVVVEozmvU5ZZ7QQvOqPK+RvArlMLQiyzuO0ClNJ0RiqBoXzz64gn5Ry+VtjXWgarI3JdiUD9Gn/\n+PK3GOBylkCud2Xw33hqV/jqiQsIFvkP7i9Elqg2lXrKeV/RBs25T8t3Cu3DAcNhkNRw/uANNTjg\nu6j2gTX+RrnBz8xbEt7ZPI5eTa+0j/NF3jcI8jWGJy+Gta4Gm2LZijG5piC24aKTWNttKz72QCrs\nfBpMeH6WKJ5DFAToW/WMrDFoXEYfEkmJ3QLnzzksss9AoiQyV1Oa7K32xgtqoao37uvPSaflOzbu\nJch/UHsIQMmktklkQJXb4HOSxR8pyh7aWWifoGUk/AlV6jFIM96OTx0CUVUuRZFqCvJPEf2ueQbQ\n4s6eW1OMes6lHj8vYjw/+XnTADBwYmD0UzRGiprgqnHT5kKlRVcoShnHds4COL9nAFrccv4X3FIs\nbpgzq/O5WS+aaaV9kipzBlp24fxjEJST/DLkr0W2Ch3TLNT24WvuoEMfC2WhxnWxXpDlGhvESurZ\np1Qom8bUY+HBT5xnjkEmxC07T5VzM9WVCdGnBLz/lvullHOLgBiV88eA9omhR6RAtVuB/L/j5p+2\nHSLG33lFfoBxo7MTGsBnVULlKkjKRqrse5zECOuEUm56SvcbqFYQUyUa55DtJcnVV86/RtUx9CXr\n1zXlfgbBWYxQIIidfC7G3/Szy4qCkZIgSuXUAzJx4tc+4htM/6UiRfUDCW6qvRhevPOQVgyKXJ0Y\nr2RoO6N6o5YNABoGLO2Cl8Ii7WMrmXpEJK+1gbjGFiP/ZDzYaHIyPC94Bvk3qUOS3Jek8R9aSJAD\nIkmHb3/ss+SdppiQsiPjXxRwd52dqRfkyPM1AoUx5J+9KayXM5LzyNA9FnyOyEylpbj0/d11nynD\nvuX8L7wlMly+Uc4/nb8bj3P3AVAU7lC46uxqQ40cRmkfuHHjH81AYJ1/HmQN86C4yu2VAliZOH9f\nGxqLOBj5FE62pcEfESKlkVkUxdv3cZJLTpI96CbsVvdkPDzgnKgd7jk/F9pqgoieuGWmfSz/HQIX\nwzOIMic4N1gQTLNqB9cOFDKEeA+wI6UvHFKJcQw5f6J92EjJhPJKRchm3o2RvNJCywtZTBmnd+dC\n5zDVxfkKBcHVfRLo+0iK/GHpJtTGvyD/WuFkDavP0QTnLefPnHqS2kmZqIxoYjZD5A9B/la5RMFr\n1OCizw2cydwuFJZR0wx3VzMZ2tbLGj4zepV6ck6MRf6N9Vazcv68QU7lzTUGUNGYLc9MxjV1iH5S\ndvvKUegcmHfds1b/xCPo9EFsQ9MQ+MkZ9+13QglPEBBiLoH17OB8I8AIUE8nN7oo+FzUPskstG3u\nkf2Edv9T5O/8cuS/lXoeQUskveLVHQD+6Uf/D/n7EPkXrb1BZQPOH4b/K/8h5GfUJor8k/LSI1LP\nR7szpbpmKqobt2D8OQNXB39LtE8it7cY/wTnuRx1qCZNucUoZS7YrS6By4Ki4EvwOOaM3XnAhK5l\naamUy/015v4iBdN9oyjf5Qj4OuBrmw0Y+gHy6WjA7+OEcMANOIA8QP65BHzZSAmqNEG0PtQIK4au\nHCvxixLkvuucCgAa4tORQpHsucUFOaIpC2GOuqh7Re5AXevJpb6KNZT3UHuCjIILJ0zHGh04I3/u\nvxR7oX2smCHEJEZYdeqhGMwF5E/5G00jah9PAVWhfSgr/E0P+w45F9+7W6HzR1Cp51iGtkcCGo1T\nSY0tXqitKsbMXYdMnHpTGdfoC/J3MMF/WVyybMLkxUMO4t1530iS1/17nYzxCUIJrMee5metWuqD\n0kveUZ0vXpycV/ksArJvFfkPaDO+3763kuit8b/gxpSKVUQ8bu86+bsNzmbXLgT4XI6qwY7BuIDD\nDF+d3Dx4CufvSPNLgUCTY/AY3I++76k2jYcbSPbSCPJh48864p64ZN+0Bd0lTaJCq7VXpLTxRMsf\nOCppAaPzn/dJkoNai4Jp8A8pkGEw3Xo7o8gxBa2dMhz8xPnv5x341Ov5vNI72i+GnkhK+wjyj3FB\nT51iFJ24pX1O73aiiS+uPnljnEBl0HIxBCagN9TkMwVikX/sFkCDfRafoxi9MS8GRvPOyDjGqIbG\nIP/333pGxp8i/yT3jEFiW6D+0/IJ5b1GTiKkKpVh8hDpPylBPOCsrdQT/VzeTXCLtE+TI5wVJHDy\noCwIZJyzgzeLmyeRQjLzuU0dot+hxc2+Pw2u93RtvmaOkcQgDm3blsJuKeG+PUX+LYpnzZ6v91RK\nmxc1Vq0ZSXWhpZj2oUUkB6F9YOJESvvQ+Wz58a3a58JbSbooMkopBOV1K76m4uVKhm9dA0hryPR9\np5vADIKVgvwbI0uzOn++dheLWgMeUxcRz95BrqwDXO2Wa/r5VCZ0Cci1lOFYUGqDhMZTMllS5CPI\nOkYJTjnhVHsJ+MJw/vMQseM4Q7Rw/q4y/vX9MaVmOWNOlnMpySB++xXfKO+T1ROaJMQBX6Z9poL8\nPRmjDL9oMF2jgeUBj+pyFCmfIP9YvJ1kjX/K6O/4EJ7ub5b3W5A/8ekD+ipFI7XNSRfaYVZzNwz4\njnsI/CxsQJCikRbaOA4ZgwlnMBfaLtOzcL+c3p3LQsbIn72YYc5CiqV0hqVEPTLgTZISLyBSh0Y5\nfzdY8Ky81RnOXyS9DARyRuNyteBxoLzKHRDKtpXx70D9MkDW8K30iRTXM7SKAI5WDXVOQWifcn8R\nu3NVAk7J881m/Jfv1t6da82OXNQnJSCt3mRuCu1Txn/tpZaJt4t/3/+26Zst53/hjXltgx648iOg\n6Mgz5z+G/Mn4d31nBvSQ9lGU3lCp50JZkGKErr3fl8G156h6YbcPLi2RbUr44JyCcnKUJByfS4VA\nR8hf5HkLC1SUGkduqgG1wpu7ovZh5B8SJo6NR835cyYwtxhL8LRQakZ2ygseoiTv3D/9PPpSEOOm\nBo+084SWD7AjFU8bREH+VVasoYMKWh6gqSqJRwukFYOpz5xzxjPe+6Ny3haRqLhgJrFeN8eAKvlr\noPZRF15RnE+96ROi5yr+O8L5tmQrm+C1UFgmYI9JGbshRtovosQfWG1y5kCrf/LPqgzEgFaM7LlZ\nbxUekkQo9619JcquAef//12n+w67oLV98kAVxF6yb43xz4MFJdW0DF2IaCkWKShV5XwD1tar7FcX\nJ02sUiqUWQHfcGnpMp908eSALy0SdB9RkD8DKisoINqMFyIqMgdWIxnPxIo08v2fQtW2yP/CmwTF\nXCOG646dovu+9aFfDps8AsdVPWt+nuuu9F236JIPAr5i0HKCy7kEf4jrA4D9rhQrmFMNmpIMo2jU\nNglcNVqR1NI+PhfOv0FC07Ds0eqX1a3kgerJ+JeJSe/G6Pw/7/xH8HdymcQLUtSmwZD/5slp5a0l\n4EXa/4Hywg5+nejlfb/nhrIH78ydkOxniWcMaJ9GOH8O8tUGKeeMwIFTnpyRqS4GA+WZeY+E4TNz\nApUdD4U/Z5RpaC3nxXgD9T4CFvk732JYNtwjwrdFW58N5w9jvPg9csA+kReTXb1And2b4WFun8ZK\nUS4V5N8sxLOSLN4KOrzUo6o9Kmuo1ftVeWvOuXqmSXcGtnAafxfQAma+NZVQB4CFjXOkvuLvS6Vc\nU4zQIcE1Kn/OA2RtYzMSB6A8lwQndA5SKrX2Gfy4hMC0LL2nchgtYuJNaAFFB5uBnBESGf9GA77D\nsepSRLevY7CcbIv8j6Ap0mPX2KceH26ehv3po5T2QZKMUesa+xxlo46+X3R5lfMfGP8UwTr/hAas\nhmHaJ7AGn1QR7L6PZWqimaA1yCy7VmrOhJTEQLJbOXShc4xS2rilDekFpdB1OcP3+29/nlx/Qpwn\neybOefg8RvuYgFxmtYgrCwLptxMtdjZXYsh53n66yPGyn5Y+oHgGB8vqgG8qrj4tgrIVZGtc/Thw\n9WOvniC965izVAIFGO0lOq5dKLmBGEwsIOmiPyhpcWL3NvlKk3qZzLKQwQKMBN9ovEk9IxMTEeRP\n4yb0BQWDVVjlHv/+dQUwQ2sAACAASURBVL+Aq9we9V9JUmLlEobJYLx4m/7zKGot8VbZKLdcPkHV\nPgwuUoo46KOUQ7gnX4WT89OC8KtFDMB8zsZfgZIEkQ1gybnk6EigNUWD/L2JU2R4r8H5YfkEl5IC\nByvJpcXFm+qprtvFU532XQxzIJY9JRpaJNSDYbUPI/8oniWgnvkEEZkC0j4txnRyTlJkTvtmi/wv\nuA0NHFCMf3RFGtbmSFU+Yz3o+ftI8JOysvehN8GuukDXcCCU4E8uC4qRCxbkHxEM8nfGIA11/jE7\n4e6RyGw4J4O/J7WP94rW+B4tiuKKhu2OGmFP13Wc8JQzHhk1E5INIWeSuoXFiQLGNiBnOX+Tc8B0\nhUVhljPenQc5R/LTQuvwc/gGOdfVVpUOYqnnInKUJB5BZlE8QQYDOUP2AOBnjqlUfc0kgx3KKIvx\nL259SuYeGS13+3jWjb8oX/FG7cNGXhQpRA86v5y2K5Va+7JnsZWtIsu44bH9Ffe8Tq7Li7eTZxkE\nr1MJXnPdq5zzQv/JXroN0VJGUOAMZ3/2oBfF1P35oWjjvu7uNojtML3XthNSqI3QS1FpmWyyp0uW\ntPF2KMPa+0Zo00XjarwpAUSlthUngPL4+LqP/wwe4UwV0+4AXNWW6Sd+jig1qso5A40v641FQv7F\nM2nI861pPeSIONyzd4v8j6BlLl5WNLqJJnbyE2Q/QetosiMh+0W1T4Moxj/GgBxrdYck7wTW5E/l\n2GI0XOVN7M/7EujljeH7GQ1CP4rMAho0rQ7+hrwJDiiJzp+NByEaAGgmWpddkphOGNqAr+sVBdtW\npG6K/BeKoaVe1SYSfDOcv6Ur2hOlJK7JlbCG+sx+h5ZURpGzpI1hXVD7oCD/7ApNlxfiCBrwbVo1\nmFLPiHIbYsrYp43uyzMT5585k3Rx96bMKDon4X8l2zhHYO+e6j22WWNFvinPwh5CSBktIlzTmoVs\niPwjXOhLgUKRV/aiKR/mX1T9Fyl4zVTESMCXZa8pG50/LW4iyyXPEml8od2bB+HK99wJuNQr7TYs\nA9Gx8W80H0S8CeXBS/KboX3SCO3Di4bx2hfUSFmRPwfROc5gOX+khCeeeXf1DuP8vKp9aJGIQ+PP\ngC8EWTylTHqMRUnkp+KZLwakkxRx5Oa2Us8jaBSA4dorKcUiDXNTgPS9MWdwwDe5Ie2TxD0tSUI1\nX8ecr5VlAkAIUYKfdtIdcN0WMv4F+fMkdgNkVjTlzg0Gv2uknnlICa1LpaQCfAlUDgO+qaS8x+zQ\nTLRqovWKGPlJBUZQ6eeYaBI2I7RUUdzY5DQnixOpYThZq+XBH8B7G2iSVyIJLCN/ypUQ5E88+YDz\nZ6mnM0E+bxblIfJXhQxr4wvnH+FxgClu+qLvh3cZMbBX1FCflHPffuYA5/dnlGRH74wlhFTJEaYm\nDVCqv+6kg2rc2G095/TcHLCvpIoGWbvUoXctHFEUMUYxNBb528a0jzfxi+E+1oxSm1wC/p6y0plO\nC1EXLV68pZqpMa5h9zR+ZPJqAECHHfjYLcTBpIYNodymXZQ/SsyG6JFS88og/6zP7KGLRlmw2nHa\np5JXGnlp1vwavqbsy8Ct2wcy0ZsDtY+ospj2SQqo2PhzcbrsW7UtAn4U+XPW+7v+3q/Q/W2N/wU3\nMXAmUt8I8m9LCYOU0bC7Zjjet153NxpETCa8F+6Ixnmg9uFMzT70gtJtBuyjb/zj8r1pUfvkMKcF\naoxWoeQcP0T+SvuEyEaPkJlRoHgz6VwKCGjRtqogcWC6qUHjMmLMmDmlQAAKXBrPxN5fSmT8Yeqs\nyDOT0WTahzIcS5LLADkSfcUSu8BJbSIJbSrOn+kJ35jA6wiVxJxzMzHvgWrXONeItjvnhOvwhQg7\nJfszhjk8onHfi8H8pl95Oym41IWXOi2ecxv0/QPA+ebhOJn2DO3TVAtZ10dMnEH+aWQhiyVrm6vT\nAqpcKuOjrlPEjQOWZeOUdqQAHC3qRPvEmEqyEi1kDlHQu/dF+2+VOVJ7KCU87LpXyHmja+FzL8jY\nLyD/YhCbMYWaidkgaUyDLiTgR+Ic/K5lEbMUjxrXRZGBIv+G1T45QrYg5Xc03yuB52wkoXQu2TfA\nFFVU5F/mp8QCWYqKuBB/yDmLl8osA5d5Po52WRt/5ngBIIWIhgotwbdokRCI9gEhPUbzz3nJ+9Ag\nYTqd0LZ9NlLPddlpIEgSj8q+vMtahIo6/Jkf+kkAgN8xO05VtE+txrDIP6cguQMgqRtrqx17LeYe\nfavZrkhF2dGYwc8BQ0Y+KSfc1zwKAHDwsCeX48KcJKG6SOgNFgok+1onrt6OJifldoeQTzCG0NTh\nCSqx4+0nuUCd9y1sZdQulkQ51yy6+m4k4Cu0T9KSCPrMhRaB85p3EHryxkjnT8+2R8F6DvgWTpcD\nuVzATz0WANj1D8fJvC8o2Pt6n2jmv32jNfSHtA9nu5ZMdU04ZArECW2zSP2E2Z56lnBVwB6kXJJs\n52QMKb1X1rI3jQoKZLN3o9YJxvEIbgKfeoRBYFgyuQn5t63WqBJv1SiDWGUDVuNUah+StxrjL/TV\nsF5+zsbgauCayy8r8k+VDLzc7B5Awoa20YXX/gSVUYkpisJv6BmCaCk/4tm5FIX2cfJOP8uQv3Pu\n2c65jzvnbnDO/djI33ecc6+kv1/tnHviUVx3ZWPaR5B/kPo4ZQefIoeTFRsWHeWyHVxh/ivaZxjE\nUk0+BX/6HpLhy9mSpjWkuilByGJcHSE4qTyZerAssfyeDCdLxidYRFkjM0a8jKwSPBqD/FkqyMgq\nxoA9dyWunX457v3S7y9f7QplwTWA6Kbpfhgd2wxMLg9Q5J9cM8ebJBdJb5cMz4QwO4fnTf5r+ZWr\nMZLXwLSPqEWYKvHGeAwS24rxL++hnTLtY9QY9Cwx0GLkvSDFQEoapros598gmfIOCeBEMsoRKYFq\ntYRn2kfjZNo3yqNCdagh5PfTyuKhi7fdRKj0gSxaVJW1Ci7mjE9PvxAAcP1Tf5D6b0+8mIWYUjKL\nOmzw2oM181wio6D0piz4CwHppOXAQWXNc48sZTxq2oeT+drWxKnYg25qijWZ8ZlTEA+dDb0stKz2\nGQnuOiOf1Vgdg66mopX2m4eiav2uLEIyd4T2qavTlgVZ50QDs5BLHGUkgztrEponWtZ/NgV8XYGn\nvwXgHwN4GoDvds49bXDYcwDcn3N+CoBfBfBLF3rdtfeF2nWMIaBBXxC6b6WQV8sBX6PMYfXCYx/x\nUJTCYosDXxC/FGEjZVAMhj9dDMg1O4XzF+6dJnH5UPfSZYkeUHheppJAxbiiQZTCf3PAt1HjilQy\nnRtBYYGQvxOvCCQbzc5pJmm3TwazEdWFUF+pUCBsPACifTzHTpTLrCgaej6+v5Qjrrr+VfJuFox/\nQ2iZnmvWR+HJOZ4iBnOiG3gwJ9sK7cNUVyNJepnjBa7RZLDQUQxokepqna0KaiR6TO8l5XQ/PPky\n7LZX4QqD/Bs/oH0oBtS07N1owN6LF5OEAtHFLRSjTl5t4zJyykhwuHryVTh4aMllSfPdKmZTc/6R\nPDd+FjVUTBEx5980Xmg7fj4eS8ha8x6gKrSpFzTrJ4NM7p6feSpjVsqDtDVPbzn/GIJkkKvahxYN\nCs4XyTI9R6vGVeJHNrcgsc6fEX3E3BXje9czfqQc1+0DtKWnIH8BfH2Vh5BiqmISDiZhjwFbTtK/\nuugk8ZJ0/H52If+vAnBDzvmmnHMH4BUAvnVwzLcCeAn9/9UAvsE5hpMXp4m6gxFTSqXUbaPIPwrt\n40ntUybIlzymDIQvePTDFxJwROPM6p9UF38KfTCGerHODSdbxWgQiBh/GjCxUA8y+GOhfWBoBwnI\neY8oJQeYP7SDv7i4rWSNKv+Nhr0irhHfSDKR6/fpOKXOhB5IocQjfM3586Y4QK7vbxAwdMa4JbvJ\ntRh/okQGAd95X5A/8+QWbWviURRjNqmQvxrMcukotI9QKqGrgvXW+DdItLcvlQ/mjVO82bSH7uUv\nHvLt6JuTOJFnclzT1s/SW9pnELzW+EWJNWWURDseC94okqT/Mo1jWrxTdyDHDXeKcykQ1VmMpuyz\nIIH0JCo29iwtsvYTVeZIKQ0Aybelhj0vvoP4GFOVbUvlOVIEx8ScGZ+SaGfiddwvLNaQ+Sixj6Q7\ndFnaR+SVSrU4cHkTGte5iB4+6J+Oc1/8z8tx/b4EnttG76PcY5H98vxMTMuO0D7OlXo/juiscn9N\nARI5IbGHRcbffZZx/o8H8Gnz+2302egxOecA4CyAzzmCay9vHEw1gbKiEZ8AfiKcf0Ocvw2K/fzu\n8wAU9zvBF3Q/UPuIC5di5ULG2BM/z5rpOgPSuSzfZ6oEA+OfkyYUAYWO0IBvUfvwBFP+W1FOO+HC\nboVTjfCK1lIQflKNuqanO/ZM+gNB/uqBkJHIscQjXJ3hCxroPmsSVNMW5O9zBKt92HggR0TrGAm6\nZcNYl92YU3G8plEFBRvMxrdFD5/13bRT3SCkUCXOPEsihZIzm5NQApVfRMstIk7uTJVfNoX+IhtX\nvpemKXJi6Kb1w2fpxPiXfZmRzIJCKJW9uexMwlNU/ttSQcjF8wKpyfK80D6q1rL7CAQxpK1TCpHV\nWiVJifpPPLeg4MIE120tmki0DwdEfVtyBLT6J5WfaM12kRKQtVLP2mvPMYq3qlJPzrBukF2LBrr5\nSpXhO1hQkdUb1iQy6jvn4E+U9+f6XUM/qSqo3E9Aov3By/uPRlnFlUJ5fDQ0/k1Cm1dvMRpvqqi+\nPotoHwBjCH4YgdrkGDjnftA59z7n3PtOnTo18pVD3FRO5bJOjX/RxXugKYqPwPpc3wAmBf7L0scA\naIcUIzpQOmTm/2JFJwSiaJy4gFFkjwDQcs19UqAUhK+BLTqpqDEAIx/1xVVvUOuwFZkxrbKI/JW3\njIYL1sHLyKVC/gMEJoWpEhkar7SPKJyE9qFB7ZsFzrOVQGzSfV4Bybhk2qdpWOdfnkton7YlNKUI\nS8pcmAQlQf6pcLLJvGuOAyQ0qjEXtQ8j/3LdL/7ch2LqE570mIeDy2BLqQPxGqMx/qUAXwvdlH3o\nxXC11aad6EJG/eftfgd5JOBLC3WW/iuyXDgPcEyp26NKq81CAiNSoTq5/6Uwm+dkxyxqspYDvkmR\nq8SUoqGMyo2Xd8rbIZKHJgXgOMlrMjGcP2Wlt4rMefxzX3HuDHsxjaF9mKJrXBQqzjnOI7BxAKZC\ne3BVW9bvK/hp4KfF+Pt+nxYJs8imhN9++404mHc18uf54yzyN+PDUbE3Nuxe40RB3lWDgInUtjqO\ndhTG/zYAn29+fwKAO5Yd45xrATwcwH3DE+Wcfyfn/Myc8zMf/ehHX9BNMcfrjOHyOcH7RhQ7fd8t\nIn9L0bRTMv5hAUGkGIDY47Hx9vo6QQeqJAqZrdnCI7+oPGssA98aYbkGITOhksibgCALo+yxxpWN\njwkYDiWvmfaftV5RNppwHvwg5D+GfFwO5XzOSz3zIS0VjVGWwlupXkCdQekApIaKqH0G8sh5H9G6\nhKZpxaDpM5syz3TO6VQ9IH4WOx7KPTs4iXPMpO+c8QRTznjYlDKuB249Z1g7qIfXtuPI3xap64X/\nVtpH8yC4/zLx8/a+VfnFnltMSgs66r/c7S3n/Ln/2FvlekSGouBAZENxHG+Qf2MSstjI3fW/fFy8\nBvYQ2wHVxeWuJ+3EyGMZ+RuFmgnuArVxZXmq1LHyTjh/2WbSZL3LImFKSkDGAgOiTMjfo52cQJcb\nuH5f6CdV3SX8pzdeX8QiNghPJZ3hONtYYyHOe2TXVjE551XCLLRP26JzE6lqexztKIz/ewF8kXPu\nSc65KYDvAvD6wTGvB/B99P/vAPC2nEf0aUfYCrWhrl0kiZzzjUTbw3xeZJmSJZhlEwtAJ2Zmfhgw\nCCwB7/nP+JpwddFze0ZRHPAtKMojSfLPn5/4ZvRP/Lry/RQqtQ8AHaipNv4xqDchGYR8P1552gW1\nDy0IpXytqmG4CJvGQ3RysRTVhX1CkySDRUE+b7z2zkId+bZaFBpweYCmyoBt2kZoH8f3zLRUVmVO\nebfs5hPy935g/NVgSvZ0UiMlyJ/OOdnhcsS9jAd55pw0DkD0EPp9KRldyjuUIXoi7eLh8XRBbDK5\nya13XDhNkX/bNEi0v4PU4/etGiQo2m7aSTFqNmBvApaZDOFC/1lOnGIacF6MP7r9AhKclvHgxvWR\nuP+k8ivJhsvirbTdUOo5DPim7NBe+QjyBE3AnYy87NhGzzyZENWVkwZ8mxqwwMQ5EmfNGzWN7KNh\nAr78mSOJsBUEMGjznDBpBA85c0DZoW1cyaiOHVFuHvA8/iNOThopza6LRzJqMlb7qBosOV8oZ4lT\nNHJ/PI6apkHvplLY8DjaBRt/4vB/GMCbAFwH4FU55486537WOfctdNjvAvgc59wNAP4dgAU56FE3\nJ9QG86IRXAuEUUbgHXRsRidtYgEYzp8SQ0L2Ug8k5wR88GV6PcP5WxRQ6tyUyXXrzlMH9EsZ0AsB\n30QUj9OSs6yjhygHmFNUKZlwslZfnUjTzKhaXFwPL2of1cH7KRv/A6kBpFnSCT/00veXwd1MKjqo\ndTXFIJx/Q1nJJuDVGqlnqmgDDpqzxrwuu8FSwYbqpZRzEtXVauIQL4yNkSQynSMT3qBJQf79gXiC\n8p4BvGL3OXhoPAv4CclyjcrIm0qmWVGclBWmMea5BhBqFNwK8s/m+7oZj+RkcB2aGKS8g6q1is7c\n+UbzSPo92I2K2IvpYwIiLd7irZLBYYoiJ6PWKv1nKRSVEhcQkuAwbRnhKjCZtK3OH+gmKK2J2Swg\nc07Cst5OZnBRAFHjsoALZ4QH+pnZkUw8dpM1neuS0Tmy8W7QeoeIRupBWeFFTglPfvRDSjXddlLF\nXIZCgSoJ0HGZZwPYXJ3V3fgGwU1LSZBjau36Q9a3nPMbALxh8NlPmf/PAHznUVxr0yZBTeq4eRfQ\nulIITfj5joy/N+qOXo0/ozXe/cqmhKcU5TyAGv9kZJmZ6YCoKM8af1b7DAO+hfZpwYKoEHrKwFQX\nV461FUnZLZ8Y/jSX4JZv6kWnIBoqGUBSTxjk7/sDOGMIy3cDPhf34SnudtyWHg/nWB/fFebee0HG\nqvYhQ41F45ENZ1+O5QW07KTQCO1D2+f1bPw1MUoMpkmi0tLWmjjDPHljPUEWBZACy4WZeDCiJwdw\nJQ7MOEEdcB/J8J00jdayJ+Pv2IsZ0D6teDEjyJ9RqtNEtCx0lY3F8OLmNQErdkJPwCvy/54XXY2f\nRCSjySCo12dxTUWnMa1VLbQmOJuoQubEe4P8mfYp3thw0xdvpJ4KWJSW0eCpgh+VejI1SLEzE2RV\nhQ1v9mOzak1tH+SKqkXWwoltQ/tQk2eeDO2TUsATHnESJ08DV544MaAQk/RJydkxah+iaiX+YIsx\nymefhcj/gdpk0jAdwxsw+EakhrGjSe0oo9OgLwBgvTG75MVVNJrfEeNfNMnMzxN6ZKPQTiSlHITq\n4DUoLcGvFEtgUc7JyMxk1RrkI5xsUoObqBqmyxkxq4vqzJZztrYJo2DOQyjIfxDwjRFXn/hhXOnm\nJVBL3+dtGHXBM65/w7SP3l9TJTGVd3P2f7tR3i1va1eeX5H/iXuvpe8rMtckL1MsTLwBW95Bk7fK\nZyrzbQj5IxTOH75FqVs0YCYbVfuIUbF0TlLkL4k8RCPa0s3IGZ9/y2vK+2lbKamgUkpV+wCFrpJx\nE7WImBM6TsdcY2JSXLTQljX/7tt+tuxe1rRmfDHnr7V95L162j0uB0lYdAwuyBvIcGUo+Ib2EiDa\nbTKp8jSiBJaJqjRSXQtOWHwAs1CrfJriHDQnitSzreJMzKm7nDQr2QAil1ntwxRgFG+q8Q5BvBUG\nSewtJqDbwxMn99H8VHmqACqUOFgl9RQptt7fELD5pkHwx4v8L1/jTxycDnBVNDg/pH2Un7e149Ht\nGve0Rv45Bs0aBGALby0GkYkLnrRaT0S4R6v2ScBdH8FX5o+UBWHB+BcU0gzUJoncbRi0JiUHUNzy\nanIxnWPcXk+ccWsloUZhUe5Z381THnuV0jSd0mcc5FbeVzl/pTXq4BsAuBNXCjXVd0bt45wYzK99\n57+k90g10gceEHP+aqRG6BN+ZpEUOvgdVTg1iPLMfmj8vX4uWbFcb8ksCJO2QRLkf0B9opRYuO8W\nfOlNvwcA2NmZYiFmYxYtTh5yZtx4Xsi8oQU5YNkag5SV+mRV1rc17ypjCob2GSB/bwQFcE739WVD\najdwZ7rQOWMMSdI50QztWR/xtmtvpfdIC14y/ddaWoaBGxv6gMYEfAEgBQUccL4ka8r9aca+5k7w\nglVkvzaJTLT/zmPSOHCtJRZLSG5ITviBe34BX95/qIwDGUu6gZMCJY71NBKnG9I+1nP13h877XN5\nG39jQC2vKYodRv6NbpLSGxpCtndMyhPaIE+ukD/zf70J+NYVCKdti8lEkT97JxXt8wf/AyauUEpy\nrYqTLTJVu0nIUKmkyIdkc1Dj4bLGGmRj6hwk8aVprPFQ5Uu5PX03J3Z2xGOR3avIwFVJaE1bchMs\nv2mycS1tw5Op69X4C/I3dFw7mSqPyhPesSttJJeC9oLxBDUGxKoZLrmBvtA+BGNFySQtBkhF2Cq4\nWO4xmECnIH9D+/BucedO3yWn3JlMJDYkyqWJBlTZAKnHGCgWoTkL2Ywl/m5OgSis1owvfZZ51tpR\ngqI9easGBDmKPZUdv1KJe4nRKyqZCI/GOVmMuKLltFXj/54PfBgvndJeB81EPETN8LWbIQ1yZ4KV\nerJCST15VgBpmYoWQ1pJpKQc6DexrJw1Sa7xrgIR2c6TFPH3Zu8p9xnmKh4QL0tpKd6URWifHNUb\nEORvFECuIP/J1vhfeOPovRZ2UwPKBZlyRfsUnT8XtOqaK4H/5jtN0S5GC+Rq54TUXqHXE51/Kezm\naHBZRN62ivwZ1WGo9uGa8N645b26y7yYuWgWBOJkpY6Q85KfULaX012LYDTNQmFF5fwnJntTlC9D\nnT+fRwK0w4Chuv5ty2oMNfQwahFRUZln6+dE+zSm7Mb8vFy6nezogic7QWm9H7eAoNWIWqpLaB8O\nkoYDMjKtTGwJSAJFsksoOlZufbluL1JGEyTkGkdmkeDqlgDgJycU+YvyQ6WwbNRlv1kr9bQyZkLG\nnMldRAJRvBX6UK7bZ0OrWFqRYjYaKDWeWyplEfgdsnEtdKhSn8zHcwE3pITH7H1C36PZdF0W6kap\nJPF2JCbFe2SYezbyVEmskgxfKrNNixMNGjp/vZMdjwVOnJt4j5ibEhTPuZ4ndvyHuSn1zGNJqVAx\n/iPIn6lamPHrmxbB72DyWVbe4QHZVC5GAygYzp/pgL5se6cB34hIZQr/5kt+CpheAVs0aqgTj84g\nf5Yp8kYPQh2obG46aQsHnp0gnGXI2rs86rVgiCxEfqgoh2msct817WOlnm4weLNrzL6mKq/DyP0h\nzJV/7ZUzzqAkKOH8WyRfDIobGLdMVRdjLpyxFxUWJUBRoTEgAXPdZamd7CzEUwryr8ssqOTV8uQ1\n/ZWd08S9EEp5ab/kmWNXxg9UDcNlp209nLZtlZLhcWdyFioj0kxEYSMLWdOUzFhLTYlaiw2Nka2a\nxbtlryH2opAR429orC+4arqwQMFr4UBYj4qluiPebymP7Er8QbzGcr4pc/45oYkH+syVPJmf2XL+\ng+x8kjoXypYAR+C4kAn4GgqFkbVw/g3HUYgKNVy+S2aR9U5KWBf5rK3+abzAMF+cP1Dkn3p9p5kC\n4QxKONvbUn3eO0Q/xXSL/C+8MYcnbr7hCEUFYpE/TZDeJBgBqNBkQdA8EOoEpeFEcob26YImvXgH\nqRfE+95qvRlFmZPcVVQS37tM5KjXSQOFBpyvJlfJ8K2NRxXIympQnPdSxpqR40JtH7r+WDyFM2NF\n599w+j2pm7IuRI7jD8IZ155Ewzz5gPYp2vi6uqOmzEd95hFtvC7eSRKjWqnXVCg755VeSINnHiJ/\n2UM2a9b1pNWdt9j4N0zPZVXDlD9MyWDYmI3KVjlQrcX6lAJR46PeQGtiA8Vgap6G9WIetRN18WDv\nhGgVb2NKNL489V+EN+fjd01GlEUFZJgnre7EVi2ivpV34Zk2ovkm3o7x0kKsEycBjVOwN+ydVWC1\nsojJgmAqfepOaGb8c8IlgITGeANNNU+khVkVh+GAu6r+eM4qCKySvIjzV2+gRfQ7mGBr/C+4sfRq\nsTO88IuZgnGOA3km6UiMv/PVIPdOV3tGcPc+6qt0M2gT6AGKykKDgw2c04ASV8LUNHYdXJPcj957\nFkTJyJ8170p3wAQ/+b5tvfThQOWFKDmz4Bl6yEoKpRnkwwFaKWlh+M2W4ikNitqnbIunEju+v8Y5\nMQBByh0bzt8YLtdOherKxmBycN5h0dsZBhGzqY7JaDnHTnhyZxJ7pMWucP4um806FMWJjr2dGNRK\n40FKb+f6PTZT8Kb3Ve4AI1dkwLyzSlli6AiPCMAVeWV2yJIY1Vb5ALb/VEppxpds4G5iGsz5s6G3\nMarK+DPA0ExekTTajck9c/4sSCigKpJCjfNLvAkg+wXjymOuBL5bE6R2Ev8p3lTxLIt+32eV+MKA\nmkIrUZ/zu6fxz/kwKSbMoWUivHw/6qZQ/JkBZyA1kg3ugvpcF/yGkP+W9rng5pn2WVAHNKr5ZTQp\nQdNcIToA4BoyMsi9Nf4JH0pPxgf+4UsWaJ8iQWP9saIoAGKYWYGiyEKNQoOg2zgGDagqr1p7GFU9\neR78SVGUxAq4pLM1/pkHv95fxWPKgDaIlQxhebd6f8nVwbemLQtWS8HdKrmGkE8acMZM0RWvgblb\nixwpSIqsE94YTN4AXI0UKWSqhJ0oBqWlTcqzFP8zgUUrAHjY49XgsmZdKDZF/tPWyACDSfKixWkM\n+dcVSnUvZC7+5uChPAAAIABJREFUZ7N+JTnQBK+5jHjblIBlSkxh6eJdxS/CzIxZQ1Ew52/fKwUs\n2fvVQKnZJwFK3UBoH1OeozL+dZJXhhOPGBK/MGq3GNG4eszG3oAs76sx5xuzhSp5FqzKcsUXIdmv\nvhcRXwBScbQEgTWQnXLEzO3oYwyoKuuZJ7PZEgd8taSzjXlE6fPop5hukf+FN3aXNYuPkYJTHXXP\nyTutcc0UPQCQTDyX6xrghfYJ6NHi5I7hT+k6nO0HGGTFk9W49DYgZ41Ck2OV3i73NBpQom3spNIh\n15tRTlZyEqR2f53tKvw+UEpEk1rELji5Mh7zBWNtXVw2mpO2bJvZIMhE/P/Ze9NoS47qTPSLiDz3\n3ppFlQYkJFECCSQkSoVGQGKUmWeMwIAQAovJbh6rMZPtZj0a2v1YDywbaNxqaIzhNdhtDAbb+PFs\njMFMxmZ6GJrJPMm2mEFGIImquudkvB8Re4qMHG7VvZJcVKxV6946N09mZGbEjm9/+9s7SC3i2sTJ\nEmccSs6/oTR9dW9Aqv6ZJ7zTEyrHBySg5zKFJfEL9uiytxMdabsbxMyTm3fSLrA/znDjbBfw0Fd3\n3jPFXJy+55mq+KhpHzgAreWOw5Jw/goFEi1Aclvh/OdsHLnmDC3eLgcsEaTGlA746ve3+lMJZNJC\nlr1VTVH4PDdcfq56UdXGld4BABYjEOcf2xZR71DlaXcroSWdc8LTZy/Gq/GvM2h1n51zIn/WCiWQ\nCKJl/T7VmEoesq6mK2MBAJezoJicxMFa7IMY/5Lz1zE58ky8l5IUIktWUlQdWwnLWMIR5H/IjYt2\nlcjfB9k1Z060j/DzrZJjAYL8qQKkD1LnhrIbV2ZqP1B66YrLjws9uYRKYp6dUKZyy0OcS3DSaJqt\n2iepTcitTBMJeSKBDZwkkvlIygmZXDFShqMsTtqg6KqG8oAVIjJxDov8U5LXLKHQlnIlEv4C99nS\nBvSuQjZcZs9WIHHGZKRYLZIzbVtrkBKF1SraR4KVvHELkOqrt3MuUyEJVOnZfOHoRwBLm4WH1tp4\non0qnL9sTNPwca1GwWHGQXKmBVQNfVckedVUYknnT5y/wxwhI/82l94WI8dtvl+Qv6F9iiS2XEY8\nZM9Nb2JCtE/Mz8pXAr5UZtsVyJ/krez9ApwNTLupmZLJOT5TAg6Seuoa/xSk1uDHO3AZFEb+Wqev\nPF+KR7DaRynE9kMjfwGCHjHvcWEZAGTApjN8xQsUUOObDEBji1f92f/Cr77nC9joti7lHW6LjScI\nD0ihfRj5z3Xaft4khQa9twMB0da5oSBWhMPKTNEx9NJD4A3Yo6acQLQPGVdBiVEVt/dxrlC+0Crw\nbf6MdP6K66aBnq8huyIl1ziVF8gGxSvkqApnpf4FzgS2tI+awOc8He5bqV+sbHAJ3fooqfYhNIn2\nwZz755zDIiNCODH+LGfkDcCpBkq0xn+xypJSzaOSl5aUF7k0BgKs2id9rrOa03GNyGd1wLfwirpq\nq4aVYnNG/jPhq9VeuDHvE93qe2mWK8i/sdSgk60EJeDrxXgrBVCTF9aYs2KjruGzoCcNoFkSWlEn\nJNEGPYpC0QFfQ6e1Uhwv3WTu45yMv9qicoD2oV6RSKEbnKcMX5VINte0TyqpwMg/qMJuMWIBj8a5\nFEfIOTsps15iIZKhmwK+gakcu9fvPrcMEk1p/T/TpvxMxTPnUiHq/aZrRVEjcXmMFl/77k9w4/6N\nr+t/GCN/muyF4XJONssg5J+3JHRq5x+N0pPLS2nsEjBs26ReWZkFCS4qFOVoUOvgDzLtQ6jOi0HS\nyH8Jc0FSvNOSHlwkdXNmcJHRY35TfSbubI6HcOA1Cs9K/WuFR2ZvI/PXHznhSuDcpytkphen1Beq\nrb7UNGh9Rv6EHAGT3k7942eeYwhJuZKMx/5VNRlmK3wdcaVF528MivNJ4ZFjHwIGJIgIpEXCLaSs\nhJTxTc+Bg6aFqsuTxxGjQv5BDOHCBq+TDFYZ/827JGajkCF5LCLLtVJd/V50fMY5Qv5pB2qn1Fqm\n9v7j3yxqFfZM1R60/FyDkipmlG8CvrFD+9AcWJrNwHswa9pntgLa9CfJLml8kkdMiFvnLBTiA5VE\n5Si2VmRd07ylmBLRc+mZKs6/LTxfAhGRpNgS40hVp2DuN7Y0lvR+Ecr4+waN8uwQJDdHCxYoMNzG\nmJLmNrgdtsafkl5KNOm8IH+vjZbzxQAi5B848t9CzhdzRcoWDluXGzU5NYqyvC+jQTg4mpwG4Syw\njwbXsWcoTlG5uCrTM33WKM4/bzIOoTug3OoIn69Lmmaic+aZAsmT0AXZVEKpkSh4uRo2SX+AojwA\nIUfalSoAfoZZVvu0sN6Ppmh8U9A+QUoifP+GlJNx3bH3B3bfB8mQRpPYlvZMVoFJpAWP0+91DCiq\nIF3nniUrdpGT9pjnZi/NBvR0nGNptiQc/UJx/pnHp8JzX3rQO4HZpuxdinfTUfs4LzGbKAuZTjIK\nqo8tPLDIFFYOiNJ7BoCPHP9MYNedq/dSotTU76YI+FrOnxfv8p5pD+aS9plt4QWPyyKAxiyBE6El\nF2Rc1UIWDe2TpMQi62xkcaF565zKVyC1j0hWiSlI/Wjk2fsALe/m7TB/+e+Mao0zwzsxoQzOVFa+\n0D6yB0QIaZGZuby97BHjf/CN0C1NEG2Uyfg386T2kRIJIstkVMWUSuYhGW2l7e9aeNxuy0wNfEEk\njJDUJhMAIf+Wd1rSnOINcRtuDjuAJ75dBt1CkD9d3+mAkhfOnyZiMn5Z9qgMHCBGjxes2Brkn1CJ\nLJY84XIgNvqcjVlQIFDGgytA+oAYGsyyFK/lhUhq4FOfA5VBpiqowfMkOZA3vfj2mc9KPLS3gUmo\nIClTdPk5pDhHTtjhxbOVYmFIi0RQyB+KT88PWv6m+shqqyjJfE1QG67TcUxFCD0RN+1IP1XOQhsd\nQhCpYkK8El9xNUOoxgfdC3ugmsKaK+GAuhehu1SdoqIkMSF/0vkTote0TwmAgqcNdhb8vH66+xKg\nWeKtDcmjpneV5sXCcP5RVcqtPX9C/jpbXDz2LPulirhRUTwqdqFpH85BoPGhYl4OEV/ZeiFwzF3F\nU1VVR4UWlH2RCQTyJkUq4IuY2APnVZ7LfIFbwPYfvsafA3wVoxx4YweFHjJvS7JM3uJNIYiEtjKt\nEhPS895juQkV469VPMoFBLj+ezmJFzlT86s77w9sOqrjRkMNWNfaye3VQAeKWIWaXF5l8xq1TyxR\nsBh0eYbZ+NMCRGoMkyFKJW2VvNWJDlsHYsl4kKEm5M+bueSdsxykRj8/f1ZQiMKJeF5XLoI6g1mp\neJxa8BYovB2ig3R2db7H1Ee1z7Aj5QaNnYYNg2u16iMtyCJPbfjcPgf/WJaYDSHnWjA/nRE9nOL8\n1fgAUV2KwlI1aAAg9ixkPm/tGCA5I96HrNaydJpWYdH7o4XVL1ZzMp9kXbt2FfvjDNc/9h35/VFh\nviheWmF0PdM+Kv5UiAJc/qxx6rkGCcKTZ0kBXw+N/FXsItM2NLac8ga8WiT0mNFZybw40Tm0goqN\nP1GAjYlZ0eIk0tY5gj+C/A+6kbvsi8kKJ8ocMaAk9YwqRVwhf+T9dp0zrnYbF2z0pXaOknUWATWN\n/Fl1U9A+ZnCRxGxhlQ3pM83TSoVL40KzISSjEBSnqigsWog0Wm67yNGgSXSNh8sJRb40HmGWitW1\nC4XI857JavJzwbA51YaRHdZ0olz6JZjrILv15T0vIAutAQN5QRBJb0CI9JwbfvZGT67ec2RVl0g9\noe6ZC+nl45qM/PUuYIFFBVKmmxdqp9U+CW2vIpj3wnEIMuocs9HHSZJX2yqDqd6fUIik9tH5EyEv\nCAuD8hNtFwvPjebVASwcySvTcRx4pcWbxiesl0YGtlXy1raV8enLMRd85z4ooErGNeYFlTYVKmWZ\nQqXRsw858JzyJAQwtIledXa8tos5govGYyQ7kBbfpvMZ5anQgq8L4y3mq0don0NpYlhpEsoAp1IH\nnlEZoWeVfaknJsnPEKAVFrFtxXWm9HQT6CmCPwplIrZoXJLiaTWBUwapM2g07cMDqVGTswh0RuWO\nghYdLRXMA6zgta0h1EEsSy+IoqVb0kIKVgXe1cq3BxRyTME9wxlzOWmb5GVRdR6yHUli1nZrVUp+\nDr7tLrSipJFgeKOQPxn7eaHUKt36dD5nEqN8EAEAvydVOVbvQQDALN5d5YvEYuYIPGaj8sgWyvPi\ne15Yrza9J0VJqus7TVWyx5INqfNKrSWGmjX5mvYh5N+uJnmqU5LeViHc1LGOIIHiHFJqRBnXDu0j\nGb4yJ8j4OzauTFUBiE7dR7GJklZ00cLBmfBqzuvAcJmHo6kkTUvxM11oeyPFGMvCePP5/BahfQ5f\nqSdamAQlRWPQNoIW3Rbb82nOH0JPBDYeaRITEmHUExW/z/EBKQLG52zJBZeAktRjqU9OhABHtk65\n+pRJbCmepF4inTgADnjRs2GFUpS+AGlihyjGTap/Ws4YBR1EVSF1Qov3ISVlAQjK+EspBokDBD4f\n7R8bspGI/Aw9G2FvS1o4qWdEFV0BWmh14TrxslKQVBngKEF0Fy3yJ0WW8OSCPAkt63v2yhACKQ5A\nVI6mh9K1if9W748pEE1NNbLBt+GXrVFfICBEhfyjXSTIeKGgFdNCke+Td0NLC6FQn4TcHeeHMO3T\nyD238HAueXhQBeCCF1pSqEq94Kl3pRLyeD4XKqr0WeDrzqPP/L7jOAqP/6y60ZvBA1B5LtS3RgLP\nKvZASXcl8oemSBlsWqmnfs4c8EXMGe7JM6H7+Pn978X2n2wGcCE2sh22xp/cZUFgYpRpUIUClXlE\nLIpSDMgGE0g1VmQxSaiTkGjHUNdkX4ZWUYtEPufqgmSFebCUVJJSKDgVUNKcv0g9HStfRMIW4OKc\nlSF8nQ5nrPhvF0AbWBs0A+v2pkPFg9IF16i2fTDIv5vkxcW9yGCajbhbuQYAeJ/ug4x/dqUR58ag\nLPSCp6guvaUekJG/DnKT8SeZLVNd1q3n4nOQ2uzJ+ItBSt9rEpqNkVU3Qvv0I3+NNBfwppR3SYFw\nwF69P++DGP9VNWYg1GZJRwCAi5qzbhBcTIFYrSZTsbB0rDX+M7WXbsz0XlAxG08LdeWeDddeMcRR\nBU+pbpWPq2BZZ67jo6Wo0aWdxji5jzygKElk8j6kMJ7R80fxpNlzUx5VOT6otk96LgdSLCTnGEgS\nmvX07734e8x+mkvQbGA7bGkfchN5ACkDTJUPQ2upjVSt0SpzCPn7jPyt7GvBxzHqiYrfJ+PKm2Hn\nAJZTahoVeF3MSV5GxtByus4pLpmQXQ4U+Sx7pOJsUU0kQdsBTRQXlRes1tI5SRUhBp0zjRd2kRDk\nqAu75cVJeQ7g573fuvhtCyjEVVIlvF0jVN0WLwYuHSvIPzrHCFoMSlrwJHEov6/iXqILXE7XaOOL\n46S2UrHgqfpDLng4FhXQvVAlyy7tUzME5CVQjSogJaKVYxbQwU8xooz8Q8PvRLJiKa/CAiOdbe6U\np0XFBEM8IPy807QP0XZ03BxUrI8X+baG/FPAmN4/eYMeVMxOBVRdOk7iYFbnT8+aZJ0iJZX+xVwA\njjYp4nfP3qKMBYodwelijnlhosWusZ6TURAZ4y+gRuoM6Zph1qsMcZXH70a2w9b4k3vGHLGieLxP\nNV+CcvPJyC90oAuZllEGhVVAxAlysLJ09yRoSJQTK1UQjFqHAkqrmdtkTtZbY0iyNqCkrPJnca5o\ngyBSSjYKjRgFteig4PI18q+pRVxBSxnagPs3T1UaAS6k17QHTOVQwEoFQ+GlzRriySX5jie/ug71\nPdUzWgA6iOgSAgyRqITSmwp8XKMXLJZHWsNa0ogp4FvWwwk8Huh5NyFRKuTq03HUhw7yJ9ChjNLC\nSSDX1rtX+Sp8LzrgmJF/4bm5PJZ1/IiVQOwVy7NosnHl9xcjdE0cUtE18UAKblMZD6W3D04hf6SY\nhkX+ap+FsvyECZ52x6fPi453hKyjySOIWXWm99jOLzMlYdH/Mx/PUmBVeNFrWrbimZe0j/dS6kPH\nvEC0VNutjdTEOc+TjWyHrfH3MSHoGu2TygsE2S/Tp0xgW6e9MjFdkBfO2n9rCJk31mqChahIgDSx\nhZMNPAnnc5W9CUVxtIL8qQyvLzh/gBCDqCl81kxrzr+J8r0SaeuAF28n52cd+koCvgWtpWgDn1EO\nnQNIRoGRLXH+hvax/WlCLioW24rBzBMmKj21Cs6zKiUrPLpUgo1ftC5gRkW1tNpHbRSu34lXmbul\n2if4RlAwLRJqAw8ufaEUZYFoO6ffnzJUSNSU5vzFOHY9t5lWLlHMoAhed4LSylt1Wk1GtJ0ZX9mo\no1ueI8S5CQyTKkjTPnAUR5CYQcsZ6PZdSR2rRgEOFZPy2uNIdXx0yQymfXyDxmm1j9A++rlQ3kya\ni4144JQPUMaotAKLwYGML6fmrEixu1QtLRIzHEH+h9TKJC8e4Io/JeTvc/2T4GTjcU37eFrx4dTL\ntRPTl4hcGWUUiCs6j6AGB7mVi0XalKNEmYLyZcJ7jVwdGf+5knUmZA2dvOUCGogssCuDJeTYVJFj\nGfB1xbOFCg5bFUgyHrNoOX+XJz8jx0buA8iTiwO+ttQ2XPkcHCfOOGjuPBmUkgZ0CkHTTzL+Ruqp\nCgKm61PwTzLBHQcXKS4hcuIQUxCyUTwvy4mJNlAAg/MgWG7Yo0jSgchCghudl/cX5F7mq3YhkzEr\n/DmKxdErzjooz01vxiLIX5BrVO+ZgtzVgK/m/J1QlRpFQ71jAj86ydEp4EXBU9qI3tA+GflTtc7y\nXuFU3+KC5Zs6sZOyfs1Y0BQUzQ29oKrgPwMiWpzUWKX3OcOc5+xGtsPY+Ke6OV3knw0tZIKQ2gcQ\nA2eR/4JRfmDap4j8M+evVTKWn2QO06gxZBLP83Z1HFDtIDNxcYNC8E5NYind5RVdVUP+4lZ3OH8o\nQxiajpER2qeguhSacq1QUMb4K14a0WZ4ikJG1zIizr8I+CrJK1cyVd6E8MiBEbShfQoUHF3AEii4\n203WKTN8nUb0jjTbUszOoOBMgVC2Mt1LUBQW5SyYUhxRAp1A8mKCpgs554Cevyi9ZlDKJaaHijyN\nzvhq1HNVJUkqXDTRPmnBo/ec6SGsCvJ33nDbBPxryJcCvlR+hMCAU4sbj1ny+NT8aQyy9jl2IJ5F\nzGUgfIx5IbHIn9G2z4XskMGZmvNaEuoLgYJWI/H4UM+PJLDSv9bkvtD5kvE/gvwPrsXIunVBeiWv\n7Xmz5FROldCtNXA0MaW2N6GAmOkFa7hEQdRFUSyZdIWUMojx520EoQ2NrudvJaWa8w9xVSl7vEKO\nQgcYRF9IBRk5+iAbSaskoTJfody5KRUBywNZ85vK+Av/qtPv02cNBUmjNv6Fhp6uScZYB0mVq8+q\nlBy8ZuQfyj6LG0611L1Cy1z0rLhnryd3pm04t8FJFc5ZXFVct+MJn64jC09QvDi/P5SltiX/Atnj\nqL4/dS9a519y/oz8lTxZAumynalTXgwbV6SALe2bAQAhS6hnWHSQv062ov6z8dcLRaX8iFPeTom2\ntaw2xNXOWDDjw6cyI1wkjmNl9vlBxX+g4mycIFnQPpo2Za+q7X5f9w8MGESQQYv5EeR/KI3cbzXZ\nnTJ6QEIZhG69Ds6qHZoA5Z5meoJpB50piBzQg+b8JZCrSwGkc+ZtDXN/6Lj5YhXeCe1TasWdQntB\nL2ZqEguyEI+FXnPrGzHq6ntCgcjEJBTsKzwmCuOhPRNGjlEj/2wUFPLn9Hu1OBHSm0EWNkLVJVoW\n93oOzaNKkJSQf4MQJYmt9MYEDAQsO7quQss6gQdQBomMo9T24c3og9Tfb7CaN7Bx3D8KDJPqTIKT\nrTGuhILZeDsVp1IxG11HBkiLN7+/ppE8EirAV9A02viXeQxQgKOJq4pCdBLwzX2mBW9Jcdap3lI0\nCxv1MRXk0IXdiOpK74p2L9OepStoTz0nvMoZsSVPCMilMhWU7Y3SUKvvNmp+UmyGyq+IF0hqny6Q\nc4o2Yylqq41/BgzK86VFdvkI8j+Elo1/dEEGeIf20S9YBkLULjAg5QqyNtjsC2s4/7QHqY9iNCXb\njzhsWVC0skT45UJNo1QM+QNj6PPBxi037nbm/OWzgAZKE04DrC2MhxPaAAoFG1UPFO2jjb/yVthg\n5kmsjYKpXUPGgw2mpX20wWQUphC4RXuyexMgyB+A3WyjuGcopJW8orx4dKguixY5W1MZGu8cZysH\nqEBnpn24XLKSenZq5yj+W+dpNBW6D0U8K0IWb+cqah9XPkPlmRZqn5TnIcbfBnLTvCh178tOGy/a\nE1gWNup/ifx1Yhtc2tR9EZ0EuU3mtAInlLcTNRDoZhAn5K+y2ZlCtTkf8KGYnzRm6ns7ODUXBRzI\n+GA6TIMfQv5K7WNonyMB34NskdJgpTiUUeGgQP5B86KC6NIXkobbxTajAOH/qEwwAATvTBA5oahi\nQVETR9MvjMwWdoEqKauk8xdDT/fIxr+dw3LG0QTkjFFXdICpREr37CI/G18YzE5AWi0K2u0tJWzL\nWFUBQ9Hks9qnEbeX+oHM3cbWKmQ0JSYGM0gQscdgltmWEoRXxj/IBuymQBdkQXaahnKS4UsUD6N6\npCzXoGrM0700QYyNz0lUmgJhxQkjf+W5Kf5bAr5EbwQsOxrbM1nUuay5LcEconoW9G7ZoMkGKiVt\n56kkM3m/jSQmxWKR0Mlg9C4CBV8LhRq9P5/3JvAV2kcEHLp/c4Osk0hDaCn4hp8LFPgh28ALlvNm\nnugMfF0Diz3gitrHa+Ov1Eg64Bty8F+qoubvuojWy/jZqHZYGv+oKBHPWmZLWSwQEBDzYU0H+XuF\nAljJ4ZML3caUsk47/QDIdUy8mkhCgYA3/pB0/pmmfQiZlcqSjlsuheVCJeDlC+RDnCyU2oGvqwJe\n8mwCf5ea82IIUah9GIXFCvJXskBvDKFXP5NnwtRZRsszJ8XaGPnHLk+e7lmuk3T+sUD+jaJKtGdS\nyls18pcFj4qhxZ534oMgf0pkSjW6ZNOPBXI12KzzlzIQovahc+qEPK1SSvenFzLxGF0RUzJeTAg8\nB9oiNhAKYOTVmHXtPI1z5zhm0+iYUg74arVO9T1nDwatyKLpeXtKQtTIHwr5+yTJ9qaUA/VZgBvP\nCVjak+WzCvmTRxSVrLUEhs4n5R99JuDMZgIDSLksWtbJ419TQer5kffju1ndeswc4fwPsnEtchc4\nKNNB/sbAiVEoqQ3kQeRjC++pUmHiOzUK8Iz8JUmsdMt1pVCmnILo/Nsi3tBVEEnCSM3991ECRSZ9\nngLNigvWhrAs78CfIxm3bsq69UxMqQqF/EsJG907/WTPhANeBeefaR+vkrw4huO71wHRPoYq0XEO\nWfA68kivDaYCA6T+KrydwMbHIn/K4NTIP6r+pQxf2d84PYtKzAZW9ghY5O+cZ+MdeYHqLmQ+zJTx\nKgL2jZ0bOjhJ2ajpc/HIankaBIAoYE/3mn9RZSA07ZMMrF6oo+b8swc1h5cig64r4HAhcHb9DBZZ\ndzn/GQfCU6VUQv6SJZ4fmroN8bBisQcEkLOpTfxBxmX6zLHUs4mW808bvCw4PuUV2j+S5HWQjber\nc04CpHqyAqwGSZ9pRYvSNwOJZ8wyvOSeJzc+FgFfgOII2iiTobF0jpYVpsAwBRdtvKFGWYnx0clN\nElwspWQ6IAfXyODXbu8Q/62lnlwvnQJ8RXArKFmbQrFeGQVx/Sn9XhCh8wXt4wMoE5I3ai9pnzi3\nCwoosU0oEI2WNbKlZ1q757JuiyzyNoYUvAec6wTvOAEIEIMEu5CFzkKmaTEb/ARywJ7GV1D8/KIA\nF8qI+KDiHEWGdvAWSOg4lW9lIWK1jxrvvHcCRFnVzNSCZ0BWDuxrc8NoXUoks0LNxTx3qZKpvL9S\nVedVwFdLJKlwml5cYMCPN2OVP1N9Sx+pDHdOupNFLO1BoDj/0jP0sstfU6h9yjiPV2OG5vRGtsPS\n+MvuS1oGZuvB65W1pmhhjT25j2jzQKMa5ZZbBmCQf1pQLLJmg6Bpn6A3cFdoAcmbaKMzcQQypEEN\nYr0gCCerk4TEEM5MkNv2Txez42dTuQ/6vyxOmjMWhRIbj6ZuFFyMgF5A8300UEiMUHVrk++0vLXL\n+ZdB7oq3E60htAZTgYGiIis/a8xzka6UzEdBTTL0IXjMo6a40v3oTGBWi+iFjBfvFCgN6v0l/b4s\nRmU5DFm8ZUz6MFM5C3ZfCZ2LwPemnytXMu3SOaRcclEWp6AXecX5u5g2Ko/KaHKsrPB2gjKkRPtI\nboNW7wlVZQOlkkEcaNGh6yrkrzdb0kCKnwPAv0vMi9Q+8ndbpNFSsNI/K/vNDx9SddR6vvr5bGQ7\nLI2/pn3KoI5sqFJ3810RPONgHHLAN3P7tMG5UxOthWfk71XAl2kfVdKZOEXv1e5gBeUkQWQxrnTO\nRnH+UJNYJphWU9B1hfMsKZr8ob13AE7RBiValuqoWlkiz7sdGNTROc4QbdWEBZJOnPtDfeJFOch9\nwyo8Eu0jBbmARPssQb1Trora1cbzPWvpbxEMZxoxB7Spjgzt/8wa8Gy46F7TTynja543LaZauQSq\nRiocc6s4a6c17zoDVt0TkHjkjqCArlcYf53hqwPpTlFYBvmD8l+ytzOrcNa04MFKPaHGsaUqVbwu\nB3x1PSrviwXLCSCauUUnoGponxDyLmiZ5ivVOiwjVkBAeRZ9tI/pc7mgBvEGGlQC0srzDYrzb/0R\n439QTXZ9csZIAGJYW4OOFPpmd96igBkWSAW7aP/SaGRqQFYQVZK3XEElWUOj6paXUsp8La+QIg1E\nQbMSBG6gE1pIohqNUaBgqk5vNwljgEH+QdEGJfqWJCHNf1eMvx7UWo2EaGISNPlKtY++NhfQY6pE\nFQZzpB3L+0HaAAAgAElEQVRXkklNlSjax0dr1I2rHypB7kLqGSBVKilAGBXyb7w3W1amLzuTDMYL\nkZIclhSWFhUYNOglViT8NwWQxXi5MOPnKvkmtJDZsaSzgfX708af5w1z/krxphcJRvOU5BXNXGEP\nQ6F1nfzIxj8GzFrxWEShJAF3Mv7LWkrsaTOXhaJ9isWJuPa25PwtPUXgbJHLOzj1HkwFVUURBYP8\n8+KEVZNL4wtaSgfMj9A+B9li20WOXeOvJ7u4a66kQFQQMpU3BqhSoZF9IQ1eoix0Bq0gf3LzFbL2\nQZWMLThZVhDRQJKSDI1yVTWnKO622oqODYoyCl4Gv4sW0ZeGsCxgxf3jEr5dtU8yZF21T1k2N+3B\nK3TAHJ7RmYmbtIKkUl8V/UJem0sKJ70fcVJ9RHnuZcCw0LxTf8XVtwuyaLapfLBSR7WK8/cpWAlo\nL1NonwUpadJJ0181heVTwD4hzfT3hX5/teBnxXiFZkkhV0tv+KKWkvMWLInx1zEbQekuq33o/c16\nkX9hhFUfmmLBC8rro2co46tRgEODrG5AGqDcidiJKeWHBeT5VWb4uj4gUGy2BFjkn95JyfkLLbuk\n+kd0cjR5Lkdon0NuhPxjNnCL6HhQOTXQqAVTv0bJ3iDGYYZ5Qv5Uo7wa8PWGUy/LM4jax/LLvlO3\nPyMBZxVE2tDPKoGrhOD0RKIkoa6BIz4dULSPrxtCuQ8bN3FlPMVL/7RyJRjjT0YhBXK9ShICFEqm\nftDE5bgJTeQKZ6x0/oxQfUFZFPdMChmNlk1iW1Him40PSNbp1DklCaqh2BBS0DI/MFB5au15onYv\nSPeS6th3F28oOqLjxRQ5C1LAz3qgHPCF7F7Hi6rO0Pb6/Qmidyiy3Juu2sfW9qncswnSqn0kfFpY\n7SY7jg0kfZY8Ux3wFS+XNqLnRUctYuzpw6n51aXNXJjxvei9hKlpcJZktV2mQXtO4oVk5K9q+5hF\n9gjtc3AttqLRBbq1dIAa508Vp4qALweThPZZwAM8EKwLaCZSQatonT9fWwWUOhm0Pg8uaBdSJk0+\nqcQBsFBGL5c60PXMjSHUhrXg/MvFievolGoRGug62zUb/DjnZ2zVPlJ8jAKGvcZfSzOLBdQiVFpU\nVWIUU0GltyO0VO18AIEBuq41rEyxmR2Y5DmSwfTesdGfO/H4fLHpeXkvdnG0gKUtkX9J+/C9yHGh\nWRJD11OYr1HjS1fIZDqi6S7ejPwV7dOEkHID0kXScSSOiFYl43ic6DpAUvYkOl16XdWZYvmz3ilO\nGX8TXI+GU4fveqBpYyU7/rXk0oUlNQYXpvwK3Z+ISSTDl8Cm98EEwsULEVqW+tw0xfzc4HZYGv+2\n3JwE3pZygDXAWu3jCupFl1lNKhCr9uFN0EFZw1rFQ7x0RileBiZfW6Wsx2ISB1fmDjhRDhi1j2Q4\n6sFPKFgQjUaO4jH4WBoP7RUJZ1x6MKHkXxVnrIPPvgf5uyJJiJ6h/lleO3RUN0pFotQ+US2C3JSX\n1KVKtLczUwuyfTa+GrwTylCDCvr7gndLdTlhzaLg2jNLKHiMi66PWXMvs1l3bHPA11KIUW/coigo\nzXELSncck+DyDorqkmxZSWzT75n3oDDI36GheyavyUk9I+ekzo42rnS/S25hxAOk0qNz2cA1IX/f\nqefvFP2CRhn/sgAcCFjK5zTHWfXnfRX5672uy6qe6fncxjl/59xO59xfOue+nn/ernLMXufcJ51z\nX3LOfcE596RDueaU1haueqsMqARd08/VmKgc4fUIpVvj710UtQ5cPmvpAkpA1Re0zyI6mbvarfSC\nrKVSISHrZPwNMmOUo6gg0hY7vQm1DvgKj0zNDyihnDGEEmR2rXWPWdlACDV49hqCCj7bzEWNzFrD\nz9MzBNA1POSRccBXUyXyTj1SmYRanEPHgCSxiRYTS/v4HuTPtAO0yogCh3OD6BdswBTyR4RrCwrE\nGFzxYozktbwXL4awey/ai5GFLPLYlr/Po/ZWPS8wehMgH/R+soLopfyEBUC6L1Jjx9J79F4bzOX7\nSpZLnsFCyVudF069UYBDgxoNGljtU+X8Fe0DCwRKzp/H56JYjNG1La4AREEFpHX/nJetV6VKqKbN\nbvvI/2UA/irGeBqAv8r/L9vNAC6PMZ4J4KEAfts5d9QhXnewlVI6zcVz2r4TI+Od62TmlWofQKgg\nLfVEBRXR97RyYgHZws6oaVQQCwXyJy9DG4HANJRSRRh+UNBoyJNTaocoBOIF5ZU6Z0MbzMR4CH1F\nyL+ciLbI1hDn34IyWAvFlEKBdH+ALDxcWI2prlI+F809awRFQe5FEaTLJ5Z7Dl20zNdl5C/GUTyo\nVWPUW6Z98qTOaqSoDCv3C10vxhS4QzG+nN3EJB3WpTd8s8RqlbKSaeqjMv7KuOrFmzKBTR+02kd5\nOyRvlTGedf4o1D7kUcc5f7/VAd/89wWCrWfUqEUDGaRV6JzqTll6npD8VcUZeOErvEAeg+VzRhJ/\n8HtSajxTtdc8v9wXR1JPvQ2mnp+3ceQP4DEA3pZ/fxuAx5YHxBi/FmP8ev79WwC+B+CYQ7zuYItt\nwZWiO6jICKW6K+ABVFIb2mVjBAXH/F85kfSxuvxBhGxhF9XgcUHvM2w9lnROp1xccSElC9bb45Wh\nYOTPW+fpe+mi4D7kTxm9zJMXbmqjN34hFAyNHLuTE67LeepnqOkrAN1aPAoB6iBf+kyhTCXvcxrt\nde65TPIqF2TPfwOS51XSPl5lGwMp+xPQBrG7h0HqF1EFYghTclpJ+2guWjJHZSGzXhEAhNmS3JvW\n81Mf4cVbVcltukJs8N3FW+/EpekoinO0+bkTPdQp7MYihYUx2HTPAhJsHazQ4dQL4w9rXPV+A53g\nP8qAb5cecor26STTgegb8VY0OMgfwnmN/KkveZ8Qhfwt53/bN/7HxRi/DQD557FDBzvnLgCwBOAb\nh3jdwUa0D5Sx1ugGECM0z8ifjVZRBkKjACpnQMgfgDX+WkHUNAaZcXEvoIL8CVkUReVgkZnWOS+p\nhBZXG9Qu72cL2WTecv6BJ20H+ev70LRPtM/VqQlM/XZBG+V8/j4VCNMGFeNfuOBlUFrnNkTYfmse\n2XL+UgBOJw6Vz8Y1Ut6BFU5kdCrBdZvY1qVAFoz8c3mHHuVLo5G/90Lt1RC9l2C4Lzl/ZbxCmMm9\nlLvUwQIW52XrUe3ZuKY7viigGpTU05yPi9ZJDScb8FVjR3l56XxC+8ydon2cbJITkPZOCEqemq6f\n57xPiZRe7TTmKwFV2vdC98mAn2YJSRLqurEVlLk9jQJEWc4Lq4LSyD+4aJRpmh4143aD2ujy4pz7\nIIDbV/7062u5kHPueAD/F4CnR+ZlOsc8G8CzAeDkk09ey+lNkwxfQf4rsKha0w9L3nUMnPfdgSC0\nj+txAeX3JshWgEk5gSrt44Ls4YvC0JTn1MiH/hZgkYq4uNrbIaOgrqs8n6CVE7BI3c+WjAeTTqeQ\nXsyUmsvfY/29Slvv0fn7aAc/kBfQqJE/ZT/Pzf+9MsI6SApkr6hm/L3QdhTk86Ey4cNMYj60IDt7\nLzOnaBElH9XolhA/6fNdNv4oSh3IIjo3C1kpTzY8sJdnXQbsdYA20T7We9JjdqGevd0VSxZQo9Yy\nap8WzsUC+ZNnJgseZfiWtKjcszfnzp3hZ+gh1XddsXA5h4L2IeOq6Mcal08gEC7Rlk6u6XyB/EFz\n3gaGAUtVaXn3DHOsInTmZ1ns0EcBcUH175agfUavEGP8ub6/Oee+65w7Psb47Wzcv9dz3HYA7wfw\nH2KMfztwrTcBeBMAnHfeeXGsb73nKQIzqaZ7mWWbbn2RB1CZLVnn/MXlrSH/TlngQIhwkd3rLvfo\nNTKrGNeSHnAhbRoTXKxymXpyLrkB2oDLXIzw382ySqwpNlFHoXBScQ6NHJuKVJB0/jogDUDRHsWE\nbec5OEkPTlQ3slB0qQST7epVJmlpWAu0LDuFqWA2YGgkXZ43PR9L+0QXgKiSs5xLVKGSiep7bGDV\nPjrZLXeMv+NVhmqHwtJqFa1c4vdXBxfey34MjUqeC1Xajt5fW+X8Iy0YdFy0x7Hax+QxdKmwNj/D\n3EEAOUjtaE9gV9A+BRVnPLQusk5jofAq9XNulvm8NcAXYRM7QwWI+ZrnpN75/gJY6L9vZDtU2udP\nADw9//50AO8rD3DOLQH4YwBvjzG+6xCvN6m1RXCwhVf1uS1FsEBW+7jCwIXuC6EXG+HUZhJ1Qw2n\nCq7lFHYaM0Z140W770stO3RFyDS4KPFLX68+OfWrrdBDXu5FAlY1qmtJoZRCEpr7Rxu/BGX8dUGy\nUKtT3kf7FIaAn28s0XL6fKaMFNNY2vhrQ6i8vSZaFGwXZFHSuPKeaxVKGWVaoy7If0YnzjdpPQTO\n0Nbo2NmxlH4WizclMCraQf+ka3aknqE+ZrWazC7eNdouCO2j4xxM+8z4GUlp6q63U56z/GyhFgyt\n3kvnTpvkVI2/Ggs0/o1x5T4r4002wATMZ/marisPRhqvOrFTLxxEAZbeur5W0MH/yvzcyHaoxv/V\nAB7knPs6gAfl/8M5d55z7r/nY54I4L4ArnDOfT7/23uI1x1spdrHKivsQKPiXEaZE+V4bQgJwSal\nisoizq3M2pQMzEVegKxLCiRU0DE0oX5O770UllN/M0gPXWqpRoFo5F9WPNXGo2lmHKsgblQjf2OQ\nQ4BNgOmqfeSdUO2VtkDL9Hcyyvlvum4/ZIImD6iLpurejgIDnfhFEQwv1T4V489crRo7RstOBkzR\nPnTO2kKm77tmCPV7pt+1F8OKtcJwdHYfKxIT5TJO1FrQm4z0BOzJqBcB5Pyl/FPV2DHIvmb8uwve\nwnWNvwY/HeRfUGSzPtqHgIALaHKcgT04g/wT7RPhlKTWLjZi/BvU4imhInWWxEyV2Hdbo32GWozx\nhwAuqXz+aQBX5t//B4D/cSjXWXO/CkrGGo080NRA8mrQsywzH6/5uqCNfwUFaLcWTnYASohwxmof\nQ6v4AB8ou7hGq2gvISmTSuTfp6bRfUk/lCFUqo2u8kUjfyqwJTy5nrgL82zrqezBe3bVNfL3VLu9\ngpZR3IcrNPTGYJYTXk0oX5nwyVUn5VI28mrCBydlBHypkFGad51fACSUud8td+5loYKfAOB6aJ90\nrq4hcJWFzCsvZpD2gYprVNQ+XIIiejQ630X9rYb8uTxHLJF/fsZMsShVV4XTT/dMz7ELElrUF+90\nLZ8P08/PUqFB0YKuQqtEJ54vL8465sWcv6ZHVYDbya5f3uUNaHisZ8+pWt4hj1W36Ix13f+NbIeK\n/G+TLZZJXhppq5r6gBgv2SzdFqDSCS6y85Lr8uTFdeDUxg7ZheZBo/szW1FlEmqconWVNe0jnH/F\n+FdULprX5t3DTMA3mJ9AqlETuLqoTYBL37eLk6t4BbTLGT0X6ifTPjpg6Gb8d/2svN5ZCiiKjdlz\nJyTXncji9dkgXeqjXhhl0XCl/NZXlBtKNaXfl5QQkOAn3UtN9sgXV8fmztk+QCF/9NM+VGqBPC9f\nSfKSjOqKFt7VaB+aAxnRF1JdfkdB3qPLFXD7aJ+at8OeaQ35K4++pH3KzHCtyrJJVOJh8rahNA81\nEGDO33H1T0t72gVFgzOu8Np4rEYBW6l75KXqkiz/tmif22QjtY9T6IhaSfswelbqAC3Xw2yFfxXO\n36vIfwWB5s9lb1Fby0UjMz9blpIF7XBAznnaRrJE/hWKp0YbGNqny/mXxn8e0/WcQ6eGSdm/Rd7Y\nxNX4V1SSfyjbtVCBHMjIWZC7oGXDkxtvp+tRsXsdKkE+2G009fNI9+dkUSjUX/BeVeu0C0eIC2Os\nOFuZ9fe5/wUFYqmC3B9t9Gqem1IuMe1T0EM8jrPH2YlfQIxrNRGQaQv1GX83IfqA1iz49J6dCvjS\nIoFKYlv+Tz5l957b2oKgFqwx2kdTgIY2U0CgGQICM+H8azGv1tTBSuBMxyQAydQ3/VOLE5vhijJt\nI9thafylvAMpJxSHX7jVbJSUokUbaj/bxL/rSoAdbTUsCoYK5Ka/dWmYdP4VIwkFrOTLcP6uQP6u\nO1irA6nC5evJ1Rn8StLaeC/VRTGEHPNCUaNj1HHyGZUHsGqfVZfdbELYyvi3ZgGtKYgqaLmC/FOQ\nzi5kJhgI0fPXJvwcAgL0ddPzUZQALTa+RP7lQjaN/7YxG8d9KAP2wcv7A4BQjK8a7cPI31AaNdpH\nFE6dqrFQlCTNGyf7EsQ+41YN+BLK7yJ/3edS6skeHwMvyUD2laqe0OOfnlMF+bd5cx3dX6DrmRhD\nn3/Ogufkt1j0z1QiLaW8G9wOS+NPtA9xiNFQExaBluhZ14cHYJA/f8fV+e9ywtaCn+kiQiX52YoY\nD7X7j3zPUlZU5lb33SKzCvIn5NeTrdyH/FNADRnNSNEto0bS3HPBGRsKRG5Cnk9F7XMAmS4gCoMW\nrkIhY+vNdAPpqCyMOuO7XPBKnlzXDkrXqxj/AlEmF17fPxmwmTmnj0XA11WQawUFa+NF97Wo3Usj\nXh0g46PjxcAu3ukaXeRfp31SkldZ24eCn3Fpaz6eNi2xsR0b58jG0tAeJMvtGsQScFjvu0ubMT1X\nq04Kp0qldAUKQQd8URv/Og7jDfJvFfIvwU81SfEI7XPoLcYcgCFe2wRS8i8FitClerXRCkuC/DVP\n6MoEKpScv0X+xhA2EhRsllbE66gMLtt3X0UWJi28VMmofpcSQLr/soyAIP9UVjdtWt/lyQEV1KTA\neY2/Vr9rt1doH/kOIX8KGOrsWUudadWN9d7SdQjF6TiHGC4xmNkwlgoZooMq99wx/gr5m0We4vi8\nkAmVZJF/xVuqLd4VtRYnKak+2wKEUF5tRerprKGyzzB9Nmt0/2TxDkj7DehFdxP2p+NmYvwJ+Wsw\n5CseouH8GVQoQ1wIOCLRPs4pZD0wFmrPz6msYhoLaszQwtc616kBBACtt+MrzRXxyqjJlp4lLaWz\nulX/whHjf1AtFkqcUssMaLWP5ZYD5jawqJE/T7iuwgJQeu70B8vda68giPH3zbJC/v3IjK7lXFfq\nGWqbQFQ4Y19D/poC4cEvBj19Pwd8QVspdpEP17GvJLno3yVbNU06XyDCA2z8iScXw2WfoXrWFcPF\n3oA2/orflkJ/hJb1+eT5cHVG9Ty5SmdBsTUFl087iBHtIyVEbDKY9gRrFI+UGtbvTxbopgANvkDI\nUmZ4bv4OVGJflfgDq9Sg319AoP1w1b0sI5Vfjkvb+H4I+dvCbjXax8ZdgIJW4VgG/XRctqrcL7kW\nU9DzRKvdSs/JBnxlzvvYDfiaeVbQPpqmLAEbjbsZFnKOvjyIDWqHqfGndHB6wZr2sSuvZP8R7WNR\nWVjaLCfW2akV2mfu1ST2A8jfKIg8v/SGC2zVkX/gBUuQDwCEWSV5ZQT56+BZlwKxtEE6zkFnMlKj\nBU+SVypcdfpPOic/wyC0gTIu+zPtQwZRB17Newk17bRGy13kL1mdwvN6Zw0mn5+NP2X4VhY8vm72\nwGCpKUKUC2+pLFN7CJbOKRPHAHmmtvhc13iV9zxn408LaCVPowAStcV7VpXVdj1GANiUjT+WNfKP\nGfmPJHkZtE7PWN+zfe6L7Jmmz0pOXc+JChBQ9KNw/t1n0HBsRdE+mvP3mooLBpwZ5F/EpVha7opF\nkU92BPkfVItFYMYEcFm1kX7OORikOTg5fmXzFjkxK2R81QWcO4vgzJ6c+lFr5E+bQ5vic3rV1wbP\nojQypEuNvm7X7a2pHfhenEjdyq0KtQeUaJ82n7pLdZU1S8p7Zs6/oA3Kstj7Y74XRsti/DWS6ks8\nKj8LBvnLpOTSCYT2GjvZOMO7yvPaAC5x9ktuYRZrep+tX+7ci36vtf0OarSdr6hVUlwm05xFwJ7H\ndlPSit33x55ZJfjs1eKsYzY6s5XaSqZ9woogfwoMG6FDbZwYcNJF/mR0q8a1oFVs8mVeyCsigQhV\nRoMWfPU+ggqsl4mB6TrdBUUEGRo82Tlbi3mYdsT4H2RrLZItd+1Kv1jXWCN/bWS2b90q5/WCPMot\n9gBB/i0SD1mWZuamOH/5uzKufZx/YWgF+XfVGNXgpylV0Z1ArjCYpfGX02lEY2mf2n6v+VvIneCf\nstOYnI+QPxXUMsh/jCqpqEVqCo9agbEy4FsG4X3FmAi15DrfA6Tm/NyvdO7FVoAdvhfxyBTKDPa5\n68+EtrOLORmvUDHwNZ1/WzNKipYiulDPLzKkPht/vufiPdc8U0v7dL12Cth24hRQi1gl0E/vyY6F\nroHmxXmmYnKsENPCCA0yut5YGfAFurSUr4Az3Y5w/gfZ2tYGcGqyOa5qSYkwLL2y9MJsWSF/SlxR\nKMCgKC/KAKAoa1AJ+N4UZZAl1UFtpyA9SMhLsAiomWnkOMT51wxhN2vWlQHD4nfNf5PbW92Kzshb\ny/6pksDqfn+MRLN5WggJtRXB1FqlSaPjpv40GpnRhNeUS3eRoP4Bqly18nbKWj1VtQ7ApYgX5Onp\nc2rjX3t/o8jf0hyAIGOixObM2Quw0d/V12sLD7g8N193gCvXrdm03fQ9QJVuRmGcK3EORv56Y6Fg\nAZulJS2tgkpcQ5+/VP3p+wgqzkdOT5LUEjjTi5jqXyEiMftUFPOymtWtmjuC/A+ucZIX6/wrxr8M\nahq5Xg9C4QEj/J8eUAs2/oQ+NEJQhnR5R7629gwqJZhV39voePK0hYs7M4Esup/aPdeDn3J7hBzt\nIkb9k+M0Oiw9qO519XX470otoifgN12qHr5883fSB7wzWMH5V0oOGGltjfZRtB3fSyXIlw62BtMg\nf1YikcHs3icgO5y1YcVcy1QdBRBGAr61DWfY0Bgvxt7zPNoYgGwt2F2sxjw3VrDQ+/ON2U2ubM22\nY8zfQlEGohafsUHgLvL3TMF0x+6iGM9jSWSoAAF+n0sCyiimoPMp7I54Cvk3pfGvIP9q/7SHnD86\ngvwPshUbVVsEWgxykoUa3W33ZaSDxJMog0SAGH+nEAKl2Os+7N9+RwDAh1qpb6c3nNGTpKRVAO32\nZmPSeClGN4BoTMGqYBcQ6i8AhDz4nTD1Be3Tb/wNcqzRPoXap7zff/InAQBm+36Yzkf0TWEwfUj1\ngsz3q3EOrZAhF76LoPuQv8Q5tPG3SqS+XA9aOObBcv660iQgzxsQ42ozfIm772YrVxfvbIQo4Mv6\n9WphPuvlWS5e/27pROdkv2pUkGuzZVf+m9yz6zP+TPt0x6yhgph2JRDUpX3qyL/7WY0C5KxbrfDj\n8zslCVXPTwV8ySPuZPNC5qzskVB/zty/I8b/4Brp/GV1zyuyQs9CbdChgsravseikGNTyfwk40+D\nxGryLfJ/yP5X46Wrz5bPRox/DYXTQGq80jkPGUK9pWHoGg9Wi+TBT9RLOq+ifQzVZdU+RkZYe47s\n9mqVihz3jMc9Av8w24PFo16f/0TIsci8dqjcc1fZoz0Epzw3PoyPKyYbUzQVnrcIRteqcgLgstFt\n2GT6NHMF8p91A/a2AmXXMHPwvxJEJdpHe5aLWBcUUGC0JvXUz6lM0oumf9KHJ+5/OX5j9SlYXrLG\nOBRUV608h6ucM5p7tp6bNa52LBjjWYuj8B4Lqk+kvde5PdRHJQ82ijZTBM7SzEO0VL8qjk/W/Wyd\n28Zf4VZo7cK6t9q1pcfs2ZDDHNu4dgD5S7GqGgpYaKknwAXRdB+AZKy/Gu1OZSlDlpCwmrQFsta/\nswup5GXMdVeMv9H5u4rxcNb4166ZuqcNYUH7VGum5wkeoTwT392sBMCFpx4H/PpH5RxejIfedSo4\nh1U0WMGqWty617bGn55bhectkRYbf1rIVc5GHgeyC1iFX4YgbeL8+VpocUDHBlTAVyp4VhZl/f5q\nizcplPJiogP2OhPYBnztHCFv1TtbsC393g56lgDwL9vvgb+74Qy8ZGaNXVNkApt6VDSea1Jks+80\njVm7YKXfi/heTU2jOf9QSI+hvMBZV5CRisiRF6hBRn9MwvSvDEibzdq7xt9sPLNB7TA1/mmQz5ja\nsK4toIxUsUtQOr4P+csL7OwEBQn48uGVIk/pUt3FpQ/5M61S1lyJtp+dUsgVFGX5b/q7Nuo0+BPy\nmRcxCWp2uzlbhdNqyCuLqO/2r4p8+HDxyPYbrr5bKbRGJTQmCGyNRzpPH+1jqZIQuu+Eq2WaOIfc\nsyD/7Elpb2IE+dcK84VKwN68F4pTrKSY0nIOOAPEWddEChZNUx2nkmYTqW4loU719R1XXoivf+9G\nzHjnM0X7qO80xoAG+zP9J//QCicLeoZonxoQqJZPMF5g/u6sgvz7Atya9lGVclM/ledUeBp9cm45\nbXcBWu92WNI+iyz1DEWNk1qmLzVTTG2E9gG6G8IDQBsGkL+mAyrGv1ZmARBDMxQ8AhS/y5yxMupF\nzRf9WU1HTRx0n9TT5C8UtE+ffrksNWD6N2D89baQRh7pHFYHqa4u7cNoWS+MFFDmICktKOndSfaz\nOnd+zzS++pD/D5ZT/GJ1+Xa5A+ncs4ICabTx993nWNtbOfji3tXfw+Zk/JecGP+UpEfeqo5f0OJN\n1FKXVtSNYxHGkMpxdzpmKx5y5u3V8XnBczbgWwvY12i7aiVaplX6kXX1ndSoqsoii9kmfCvuxP+5\n+kQ5h05yNCVDtGdSqJGqnL/QnuW96tYsdeMO690OS+S/yGqfhpACu4tdTTQ1Y9DKQR+WgcV+6IAv\nbeCgB2yH9qlU4AR6kL9zmEVbnRGo0z6xgvz57zy4ugEvjRzZC9BBWTIeVMM8as63KwkFusa/tmsX\nAPk2IyA14CuDX04hxh+G83dcY0eCu918B1+hfbR8lmWQM+LJZZ9guyDLd3YfexTwr8CxOzbn82qE\nJ/f8zt3/Gdd9/oO488pOcy+hqGc0a2ZMtdSS9GqyVV/w34AAmmbzUQCAz7R3wQncL8eeiPG0CuRf\nLaEu6rYAACAASURBVD+srzNkSGvN8OwqbmT2tSVg0HSPNePJem6xhvwrwgPxIiqeb08Q+t77/wsA\n4CX5/4nzpwxfPWdkfDU6DhNL5G+vZ+1P1x6EStB5vdthifzbeTKiUvCsQr0UiUy2jnnxMpr8IniD\nijrfGb111dIYIOQvLbiK8Udd/VKjrKROfAVZ02cVTbirqn26yN/vuAMA4Dfnl6p+9NE+Fo3ZmiQ1\n2ofQsqZKhmgfMphlDXyRMqKCRnnRMMY/97WCqgNLf7UH6JSiRa69spzGA1EX9b1hgZtmO/Hn7T2Z\nAtGKMkMPBTG49dr93YWVd6Sr8Ohu67F47P5X4sWrz+G/LaAAix43BW1XKxyYfucL5352x1et9b3n\nUM1K78Y0NK3CqqDa4lSqfWrvpCjCVp5j6D401WsLxHUT72LpkaKWhFbpu2rhCPI/uEaF3TjgW+FH\npUgUIZoKyqE2WwH23yCcv+Hv5dhFSfs4Jzy1MZ512keSvDSiqQR8+Vx6AJW0So3zryR5mThI/s7y\nVuze904AwG+r/lHTtU1Q5DaEoAKGBvlTpVVbGiH9OkT7ZNoArdX5e6ekjDXKydI5gDaY3TiAKGR6\nxoFReBQbsht5ZNdgNpQBTDWcStrHOxyAB7DgsVqjxbQXQ95juZMatetvtwcvvvfu0XuJJfJ3QlXa\nOVFw/bWtQyvN0o9qwZvVchs08idvrushVtU0HeOqv9edg65cLFDEboqmYya91TfzuRZV5N+Y+7JB\n4+51Z8tHjP9BtUUO+DYD0itdDz19oA1HYZxpoDSyQQX/yUwki/xNHe/CcJUtOidJXiaDtsv5l8W4\n9N+HJk1VLWKQ/wDyobhJdCapiYwATzquAGprubDxnxWGs7jfsnFA1kWzKNZpny6iN8if3XLFnTdE\ndcmOTdRMSQ7D+dM9UMC3YmgAzg5dIuSf7zPt22rpkA7yr92L4fytimwevaEj/uYlD4Bu5l5qi3cN\n+RujbseX7v+Q0bRlvRXdVolz1OIIRvXSoX00+OmnAId0/uZZDCxiOuAbjPHv5l6AvX3dPws8/Mh1\nZ7Olzmfr3Q5L2oc2c+GJnx+uCVryZuw1lFMYo+POTD+ziqKPJ2yLmj1G7aPd/Krapy59jBXjX/Kb\n+Uv5I+L8ddZvVq5USjpb+V3/cKjVUwHEfeeSzj1xDjL+jqt11g1m2XR8xAanJbdBEHiXItClE5pi\nI3VAGdvNiZf/Urub/xb7DCZ5eDSRe5A/0XtkqGtZ13xvZW0dw6nn62jOv9gfoYUbeoxWxFBZyPj9\n9Rp/On5ttF1Nuw9YL5THcSUb2yLr4p7NPCkDvpVAboVKq9b9qrQk9Yyd41xllzPJwB9Q+1RiGbo1\nA3NxvdphifxbRv6WEzYUR5ZzeVR40BL5X/p7wDV/A2w/vvN3mzDTVfvU+NM+qad0TvclJxTp+xtA\n/vWBnqmNpmv8+wb/rz7sdOw96Sh1/h7jv5TumVQytPFLPqO6wZj7QFU7uy5+rdkaJ9Z7Wi0TZyrl\nATTyDw3ds/aA8jk3HYXLD7wUX2jvhM/nv9mtNytBPl5o64aQSwMQ/1NTlpTXYg+quzjqe2Hjr1Cm\nr8SSqPVSWAXt03iHn9beX0nbVfYTrrYees8qnOg5VoLDvmJca4mPg1LPyoI6EvAtmy0qqL/TvXdW\n9pgFt2AYepD/37Wn4wL/FcxC/7tcr3bYGf/rbzqAv/zSt3DxDGhoC7aa8c9ZfNUga+kQLW8FTn+4\n/F8bTJ32H0qdv/Ys5NrLTdfY2TRzjcwytWCybbsDKBbI0dbx6brCumAVkOkcNTmfc7872/5VXFkA\nmM1oj9PMZ3uvqDT1vEHG39bFyR1DX+vT0OvtLGvlK1hWqRa8piL11Ajsb9qzzbXp/HOlAEpfKvbk\nrWnWIQa65RIiGqn2If8u7eMr1+E686qkwGzQ+A97MVwBtE+hRsafF2/9rPuv6yqLIVDsPkfjsxKL\nqZU5iJNon5rxV8+Pru+1IR+gfXRhQ/2Oi02AUl8qni/TZZU8CfX7kw/8Ohos8KkjyH/tbbkRbm5l\nqZ/2aTJFIzz7NDe2/LuZ0KFQ+7ju3p0AsHmpMqD7kD9lkyrjX9YJ0d/nQVbhjOG6hokG/wJ+aA6r\nrEp70Cwjf9koRI4x5aLZeNA7qdMBZfM9Elznusi/VhhMJ28Rcq5u7pPbw+8uGnWR7BX9Y9onG+Ue\n2oeeZxsrdEEv8rfearpMprAqAV/tkQ3Yfr4X3W9AYjBzqkSr4lTVmE3ugy7jMRQr0gZV3/OsqTyL\nCufvy7IbUMbf0CqF52Q4/y61y+OqB/n/0XPvhR2bKrkIxXE+dLl5sTN6TtPiXpE6q3M/9O4n4v3/\n8G177Q1qh53x37wUxFCW6gCNvpfTS2uKY8vjas1q3uV7ByqPs4aYNy91J0ufW85bKyqxaK2qITcK\nkGrOvxJQqxuPceRYymBnWZLGyJ6VK/Y+qLEB60HLZavtS0CNpJ41BUXNoISma1i1Qf7H33iYoU5q\nddkByH4MvMtX/d3RGxPapwd9q2vVKoXSZ7OqIRRgM/z+5F70PQr9ko2/c7kGVsn599M+Q++vz8jp\nuJd4q9ozpXfaNa5S70o/95L2qXjSxvNYtt+Dncvn7d5prlkrAw4I+LHHhs53HBv/wgOAHeNXPels\nvPIxZw6+y/Vqh53xd6r6Xomi9GDZlg3wDcj1+odon7IZIyrHHkA3JVtKEAzTPqaMtO4L0z4L+WwC\n8q+Vb9aTlNUiSgY7hPxrQTYAOGprSnTatTnweWv3TIsXKXRqm2nXWqhtbp4bBXxdRW9fW/BmpOgx\n70/TQqVB7tKF6cAsw1ukpKkaPw8AJ90uUYu335HLO5gkNGswy5LYtW0IayhYvNphY0F/1/WtAKHt\neP+EStkMQDCsxGym0SW1TGXAKt74HRsVTYW+ya1mXFGge1cLKOtPGuu9AV0vsLgTdSk5bmW5vjET\nUNBSZQa8oT21bQhY3jqwmK5jO+yMPw7cjF/a9lFgH9SK36Uslk+9L35n/mh88eTL8FB1DNCjctBN\nu33aYyjrw0APAD140u9n64BqH8LNCD4Yzr9i/LNbXzN6goIVYuGAkjIKE5BjaQi3bkqG7ZgtWTLp\n6rQBNVHoVAx1pVU3/chtFaQ8If5Wa8/pOgptzrqUUy34To2okkVpPGaF8a9sDwgAl99rN44/ahMe\ndMZx+bj6IgEoqqAa/MzIvzK+yvLefY2zwsuYzRIZf1W+u4ZcC9qnFlOqXrcmrwRg9/PtKntchbaT\ne+kGfMFzIoOQitRZNxaDmLncfx9aaaY5/00141+hpeQalYDvkOe0ge3wM/6rN2P7vm+m3+kl+O5K\njNDgCS95M565ycYFOsfVWs+A7tueEeguKJ/81QcaXs8qS9SkCzXO32rrU58J+eRJY2raVFBwEQdY\njKlF+owMSTfpvz2VTJfdHIjAqSccnW+x4pnU2oCkkIyy7MZV98iosQCAcjyiq+ZcyPl76DXK91ik\nzcq1ZtsZJOlsnZsBhRMHzEPF+DP/XeOBpxn/WrExADh6e/J8j9221DnWPm+r1nJ9c6BofQbfHEPv\nzby/7O1UkH9bqWvEfeWY1zC4INqpd4+B8ppG5CHnXlmp1f6nY7vXrXH+Q9fdyHb4GX9tgItsydI1\nPna7enETdctAETAMXUOtW1sOytyO32ErBxrkX9Fh15B/1Z0lQ1ibnDXO34lRGPJ6+zh/FPesE5Z0\n/6j/xx9zNHW0279KMzWXUBpMMv6kIBrmofUuYgCVPBhf8Lq0Tx5jOZPcq+BlLVVfrq+9O3scoUTi\n4KsLWeWeehfl8rie+MXm7Lnt3CTXKzcbB7q0j5v4/oYWPGqcyKdlnfRZVU3TXZRZVss5LV2JqG5N\nAX7G7sN65nK+zSuV8s8DnpMrs8PThXuvu5Ht1rnqRrZGGfRCVtVbpz83kbgNH+dMpqWa+Nlz1in3\ngshHONke2qemI46lygUKOTZdCqRawbC41hjyrxXTStfJgzkq2qCGHJ/5/wB7LwNWEtU1RIGY0w/Q\nC5yYRGi5WRsVMebh1eqyAwCo5C/RPhMn8nBKPxl/CojrJL1uoJpaTflSa/T3tkxg5PcnMaXa++Md\nzWYV5D9wz7VM5bLxc6nQqZ1NdgAe2zXkX6suW/MspeSG9tSGjH8dHDaVTNzaBkwc/m9qAfMjxn99\nWs1YMuc/1TUePs4WtZJjH733BDw1/id882kfVefsoQ56rp1PKr9X1A5EY9WSvIg2qFWzrCJHVYZ2\niALBGPKPipaqGf8TzwUe+0YZ6MYLGUCOA5te8FYMRI1NVaDwPU9bkMsgN/c9Vjb3GDSE4wazabpe\nTC2OU16vE5coWh/tw+MrdqXENcBCyNUa9Ym0T89xlHlug7vWq9NtmPPvfq/mjbHaiAQP0Y3Ef3rG\nVmXTlWrMJD9fStqcWt5kI9vhR/vUBmyf+160TpZsX6uVSQBw52O24h3/8fn2nHkHq7Egss46Na5o\nTe1QoVXY+GfjUdvBqvZs9MI4BB57F9Aa1VWpalg2PzHga4rRudL4k4tPCqKJyL8nZ6FsvWqf4v99\ntX3KZox/xxCmcy4R7aN396qoYajVatvXL06AoW/xlo86OQeqnXj7FLzuA0CdNuGdOI5z6DyGfuNf\nz5K1HL5vhp61UhspSnhKzKtz3cq5eaHQQW1Suw1UoL2l2+GH/GvNT5vsgzVNKucDhlFrumad8+8c\n1zO4qsiHaCxdV4i8ylrwc6hgm0LBg/w3B3F7aB+dh8ATsf98VSlqpQ2jahsU9DolfhD5B/Xt/tar\npCHaZ1OmsEy8aOBeBgwh5SBsWqEtH/X7G6ftpgKbziLBXoyWElcW74f8H4Dz2LH9qNyVicZrgqRX\n3p/vHBtqBc5qtF2mHUnGa8FFhfMnKaka/4PMmaFluzE53dpKHgKpu/ctul7ckYDvRraJE2SqoTYT\nsxl+cTWUXj2uplkGqoNL6oXr15e+Q5mTuiqgG0oVVyh4CvLpp31GOP+yTZTYmdhAB/mnNss8ue7/\nlHpBTsPdSqsFFgEAJ10A3OdFwIWpXn4Y6KNufoAqOWrzMvBj4JgdSX1jAp0V2ar0cVrAtzdmU6N9\nau/vXr+U/nH/h5VV1eN6ng0/P+3l0cZCFc9XtmCUjyKNP5JG6zFfMa5LhTfVTox5pevqc/cbfxMb\nyKdmwFbJ47il28+G8Z+4srYuZIpmJOCrk6VG+DrSV4+94Kjq9utBWOc8iYuWa29ZDsB+YGmZEoqm\nUSCt4vyHOM9eQxgqyH8CfdZXD2ctx9F1yPibmMVQ8I6R/7Dxr1VkTReaAZe8nP9b3S+20obQ8kre\n8Dwwp66M5sDiXdvYpH5cDviW47USsyllw7U2tg2hHNeP/BcxVcokitKWSs7Gf9ZP+3jz/tLvUjdf\n9aFyHyuz/Nx8fd6VrZ/2mZaEdsddm4B/Be57l+PMPfT175ZoP1PGf2yydzZB72nOIJQxRE/nHDP+\ndWTd1NLHK+Vod25ugP3Azu1b0/dMHZhxt7yNY/3rCfhW1D4cHB7k/KcFDKt7vVKfCuNvkP9gjfmJ\nxn+iUGBqwk4YjHPYAKRruvw3AODOlyTPo7je1D52358NXgMasAy8P1NhdNoiX47DFml3rBWqD1UB\nPU1F8OAqaJuRP3H+PeUT3rD3T/Cuz1yHvyFqMgjtM5zh3gNCankIFaA0yyenRf4I7XMLNccvY7gx\n8i/lcEXTgziMvbgenX/ZYiVxC6inj6OCLBraoo/yAvokdr/898DKdnWunPA0VSde3kcF+cOl/w5L\nAHuMW9H8QMCXYjhLS2T81fcmaM8n0z5riAENouVaEJ4/IONPnLU2ruqcT3tP9Xtj8SzJ0O55f8r4\nE6KOkxH9gBkZoPeoz5tznS3z5zx+q8if1EEq94XBB+n8nRkM/OvzH3s/PP+xun8yFgZrI/Xo/Idp\nnwp9mxMDj0g9N6rtvLP5L9dLWTfkr3T+o8h/ovFnNF8G5PoLR5nBmjewIQ63afSkUwP3mLsA2yTr\nVLu9g62X81+y108Hm+/Umvc9/StaGMgHWMr3uNSM0D6nPQS4q5Tkjjzhh9tUma7Ny+g/qzZ+vmMw\nC+Nf2XKz1qYuUL0lB6gSbfX9TQxeD9SeH6J96Dory13PjRa/ZkDn79SCJXObxAa6DwO0mSqcOIz8\n+zj/Cu1TAxen3C/9PPZune+NiUY2qh0S8nfO7QTwPwHsBnAtgCfGGP+159jtAL4M4I9jjP/uUK47\n2p72nmp0fnyyTw34roGvWyvyLwzNji3d9PGq8SfkQ8bf64k0HnidVBsGFSNDyhcTMBxPbDPU2RDy\nd8BqDJi5RQf53/+uxwFfgRQlM7SPQmRP/cPipMQZtxhqU4OpfVsVlq1aeK48BxkOvfFOGDL+ExPW\n+mI2m26Xfs73db80MX4xpCbTi0Qo7qMJHmil7EYwlT7T96jwXO3a+v3R41uwA9A919B9JOM/lfNX\n9zHb1DmW4mg6Kx/nXwmc8Whg23Hdc/wbzfB9GYC/ijGeBuCv8v/72qsAfOQQrzet3W43cNRJ8n82\n1tM43rGArwnCjqzak5FZz8Jz5km7uuekLEbzYR5ooYuCh/nvaQlP6KMNjjoZOO3BwBN+lz+asojq\nWMkgRaPLRRRGZsvWbemX1Z/m82g3e2DC0+R008bDWtQYw3sTDMRh6Huc2dqt3V/to6dtGKfRdp1x\nmLevpGcIAM4R7dP/DI1yaehZD9Rb4sWAFuMKbbd1U43zp3PKF7YupXMftaUWIxsfCw7tsPHvC+ov\nbekeWwObzonhB4wX+29V5/8YAG/Lv78NwGNrBznnzgVwHIC/OMTrHVSb+nBbRtTTaZ/RVTv/faw+\nd1+OQa1eUFVHzzVD0s/ZSM0hPtdk/pvOV1G+PPVdJgg5hT6bSmuk85FhLPnqPNFzmYVg0N7AgjJg\nrHTrVTgNtYOUevLiTQuTpsWaita97ONU2qeG/M/7ReCy93S/NLFO0dDiZMuIl96OBQmW9kmfbVvp\nvit6f/pejs9lsy869ZhKX4diEkIBDj3CtSR5ya5i/eez/fu3afyPizF+GwDyz2PLA1yypL8J4MWH\neK2DbxM5f8lMHQn4TtR1m7+PnHM19qDlSkCpxmtiOaNgrjSp+zuwK1BVNtdtvbRPpbUTFrypnD+g\ntmssr03PlHYR05erPrf8p8nGf/o9S5emKZc6VNzdn5B+5niMoS0G+js1ZiMbnBfvxDngkVcBJ53f\n/dLkQPxUqqs8ziqcLG2Xfg4afz3G8+JZBW4Tgv8e7UiRv2nSZEADqmnW/zar9nHOfRDA7St/+vWJ\n1/glAH8eY/yXMfTrnHs2gGcDwMknnzzx9OPNOVndh1pfBc6y2YqB05QgU5F/53xNl/Nn+kofe9qD\nge98AVjZ0bneNOQz0fhPGNCMyIb0+7WS0z2Nnk2HvrroBcAPvw7sfWo6j6a6JhrhoVYrnT3apga5\nS4N+8a8kXjhz8HazkyHPjUqSjyUwdhOP+hqPBdc/boyEc+BZD3H+3Oc8xvU900KwXEmipHiOGYun\nPQj48p8AJ+ztHj8EfiifwA1z/kM7ymHXqUmCm5vIu/sva89963D+o8Y/xvhzfX9zzn3XOXd8jPHb\nzrnjAXyvcti9ANzHOfdLALYCWHLO3Rhj7MQHYoxvAvAmADjvvPPGlJmT21S1z1SO1x0E8h/k3dNJ\ncx+K45a3dg+ln7qbD/h1YM8TgV137h5fU0xQm2j8cRAouB1A35OlgkgbqAMVhLntuEQ55Rb6Ar5F\nGzJWRScBrI32GaabBoLc3kvwFfZehjy3WFG+1Fov7VPrJ597GqIfLszXL/XEbDOw/8eyJ4RG8gNT\nUGgfddA9ngac9fNVDn56yen+a5pnUc6B53+mODYn6vWfzvZh6nhc53aoOv8/AfB0AK/OP99XHhBj\nfCr97py7AsB5NcO/oW0q5z9R6jlWK9yec6KCiAdAifyXgXOeDpz1+O539PDyHjjmrtVzTzIeU43/\n5CGNQarLT1T7ACqGMPIeQ5jm7QwtDLpNFQAUJ5/0tzGqy6oJh2i7iZ4b0z7Tjb/uxOrqKq677jrs\n25dUQXGxCveQpKJa3Bzxoy9/uX7d+QJfzse1y7vg9XH3e1NSGX37RuC7X8Zi0fKx8R+/Jt5r/gz5\nu0snnI0vP+QPseRW8OWe6+rvHbOyrfe4xfY9+Fe65te/2uuhb97zOHz5bhkHf+Ur/dcEcMreB+DL\nZ52DuZ/Wv2blmOHjetrKygpOPPFETnJcaztU4/9qAH/onPtFAP8M4FIAcM6dB+C5McYrD/H869I0\nrzfUBPmPGP9a3ZX+i6cfI+c888RdwA+B5aXKK3n064t+5gDZyP1IF9eD859uPHg/4QGu2g8hwqLx\njl0jxxnkP+DtVGvEV5rc8xqQ2ZBRN2h+ZCEzMHjIc+vu9FZrceLYBtRCoq573XXXYdu2bdi9ezec\nc2hX98N/P8VaVnedhtlyV/IIAD/dtw+brk/HtTvuCL9FbYzengbs+zErjvatLrDy/RSzao8/Q2iY\nH20GZluBLUn5dvMNP8Dmmxrc6LZi6/Gn9d/It9JCdcP207Bja9cjAIDVG3+I2Y+zJ3H8Gb3G/yc/\n+Ca2HcjExgln9F8TwPU/+A52Hvg2fhq2YdNxp47276btd8KWrTsGz1m2GCN++MMf4rrrrsMpp5yy\npu9SOyTjH2P8IYBLKp9/GkDH8McYfw/A7x3KNQ+q5Z2XptM+wxNzaTad848TaZ9tm/JeqiMUCADM\nc03wWbt/9Fhg2PjLwjiG/JlsmnRNQPHRlaZL7o7d8yJ6wI1nU9d04vVrT0RKB+HtTK3TMob8TcLa\nhHyJMdpHlEsTYja8Gbr0cd++fWz4yz4NxrNMDkTxN9+I1HSoHXXH8WMG2nDgdWJQdo1XXNvRazse\nSM98165d+P73v7/m71K7dSINt3QL3U2qa41on6EsTUDKCeSDB49lTf5kVdD4QFhk4x/i6uixwIi6\nhcvjjrQ1cf42Yal6WZ3hODHgO4aWGxPwHVh4JtKAa0HLct1peGrMixkKPprrrdGLmXIvrK4qnrfr\nMfiDpbuVYRszcg7AvjjDPPrBIyWwPzEsOGj7pz3ntVB/azblB1nVc0xEMtZ+Now/7TsaR8o7sIEb\nNg7LazD+LHscMzhcpnb8lXxzOQV1f3C7rrKh1mZDBmKNmvcpQ5tpn8EkoYmF5yDGqBlZJIxaZGqx\nuIEmG4VPp32GEop0G+NpR/CHOpCuNwJsalsf9h1bLRk+0A4W+XeOBb4eT8SX4zDSdxPlrWMX3rp1\nKwCHb33n+3jCs148aEzfePV/x80/lUS4hz/84fjRj340eLkNXC7Wpf1sGH9C/m6E858YWFzSlTbX\nS+3jp1FOAPDPm87Avfe9Htee1A0C19pS039tWpRG6YCDUPsMIX8t+xvMQwAwRzfrtdZs0tsQ5z+V\n9jmIDN+Jxn8tFNbg9UgpM3JcnEhpAsCCkh1HMq/594Gr+4nHpb+nJWwUzy9twXfi7fCjWSetCIvF\nonv8oIQTOOH2x+CP3vyawUv+1//2Ztz8UymB8ed//uc46qij6udcK+1zK9Xz/5kw/i7XB/EjvCjr\nyUcQz2ygzHDZmEoaGxCM/KcNhG/h6FG6hNps6LiJxmpqjSJAJd8MBnyn6cQBQXjNGiRxrlJzhdqQ\nbl63g8rwnfw8R3Nepp0mTEP+WINyqTevwp5Qfhs0rmsxbMPnvPbaa3H66afj2Vf+Ii55yKPw75/z\nDNx8883YvXs3XvnKV+Liiy/Gu971LnzjG9/AQx/6UJz70KfgPo97Jr721a8BAK655hrc6173wvnn\nn4+Xv/zldCFc+y/fwlkPvBRAWjxe9KIX4e53vzv27NmDN7zhDXj961+Pb3/nu3jApc/BA57wbADA\n7t278YMf/AAAcNVVV+Gss87CWWedhd/+7d9Off2Xb2HvfR6CZz3rWTjzzDPx4Ac/GD9VnsPBP6P1\na4eq9vk30VymfcY4/z6us3O+iZt3ACo5arT083RahdpUXng2UHVxKBPWtDUFP8c5f7PD0yjyT9ce\npK9y+2x7Ks7x/zhC+6yN818L7TM1e3iq/HisccB3olprLfGLvozX//inX8L/+tYNwIGb0gdLf4e+\ncRsBuAM3pv80N/aOibudsB2/+rBhFQ0AfPWrX8Vb3vIWvO2ii/DMZz4Tv/M7vwMgyR4/9rGPAQAu\nueQSXH311Thty4341Gf/Ab/y71+Aj3z4r/GCF7wAz3ve83D55ZfjjW98Yz6j7feb3vQmXHPNNfjc\n5z6Hpmlw/fXXY+fOnfjN174Gf/2u/4ajd97OHP+Zz3wGb33rW/GpT30KMUZceOGF2HPOubjTMvCP\n/98/4Q/+8Jfx5je/GU984hPx7ne/G5dddln3pm4d2/+zgfyJ9pla0nkyPw8MpsCnP6e/H4hj56S/\nT89tG2MGvtym4nZDyH8qTTG1RpFug4jeT0f+J+5MiW7Ls3GDedmBX8M9971hkDaZTPtwdvYEnjyO\ny1tNm3DOf2m7dWrKNrZwUpNYxHSd/1TkP+Vck46dcPBJJ52Eiy66CABw2WWXscF/0pOeBAC48cYb\n8YlPfAKXXnop9j7oF/Ccl/4GvvOdbwMAPv7xj+PJT34yAOBpT3ta9aIf/OAH8dznPpdLSe/cOaxG\n+tjHPobHPe5x2LJlC7Zu3YrHP/7x+OTf/h2+0p6Ek++4G3v3prjcueeei2uvvbZ+37eSGf7ZQP6B\nkP8Y5z+OWNPf10A/5HOtthM5/xFqCpg+oR5z4D+hwQL/MGT8J1Ip1UqFPY2e4+Adq2c4FvzcuXUF\n+NGERRnAzVjBzVgZNP7NROMf10CV0JI9hvwjXAIhE4z/zx14DRwihlKKBnM49HXpXiY8w38Mp+KC\n1b/Hgc3HV//+vz/qTCBG4NufTx8cf3bv/bQxwtNxO+/E5UdqbXUxYewX74L+v2VL0vG3bYujoW8d\nGwAAExdJREFUjjoKn//85/GN676DLW4ftuy6Q//3ixEdY9+mLj2eTY+IJAJYUhsxhRBuc7TPzwTy\nJ85/1DWm3JZR5D/d+FM9/s2bazV69Dkb24mBRqqXeTt87AHMRg3henHUtRaGAuzqfLOBqpX54PRj\nDc+9GbjnyRmRa6BKiA4bQ+Kikx+/l/1Ywj5UdnJTjXIWxt7O1BwWAHjnyi/gsftfiZt23m30WIxc\n/eAY//72z//8z/jkJz8JAPj93/99XHzxxebv27dvxymnnIJ3vetduAkr+G67A1/8wv8LALjooovw\nB3/wBwCAd7zjHfmi9qoPfvCDcfXVV2M+nwMArr/+egBJGfSTG2/u9Oe+970v3vve9+Lmm2/GTTfd\nhD/+4z/Ghfe6aPI9V7pwi7WfDePfkM5/akbsGPKf7jDd9fikCDj9+LoyQF00/zJu/InGOTCfdj/D\nl53GGQsFMn7Oty89Gd+PO/DjXdOkqNNr7ayBex8w/puWRxZiPsm0goCAzmoeW1jI+K/P1PMT35+U\n2R4/Z+sCPh9PHQYNUwPS5rhDt3JnnHEG3va2t2HPnj24/vrr8bznPa9zzDve8Q685S1vwaUPvhiP\nv+ReeP+f/RkA4HWvex3e+MY34vzzz8cNN9xQ7dOVV16Jk08+GXv27MHZZ5+Nd77znQCAZ1zxNDzs\nsudzwJfaOeecgyuuuAIXXHABLrzwQlx55ZW4+9nTxj23IwHfjWsuF0f7i9kD6hsO5MYbwU0Ozk64\n9sTN44X2GTf+SzmAuy7GPy+MjatI5MyBVBxvvH1pdibO3/9f8bsDLr5pUxfTdUL+XP56pFV3TOs7\nNv+cWjpi3Yz/5Aql9P6mG5qJYrJ1M15TTuO9x9VXX20+K7n0U045BR/4wAfwheuSDv9Ox2zlz8lr\nAICXvexlWBz4KXafdAK++KFUILBpGlx11VW46qqrzDmf95xn4UWXPbR6zRe+8IV44QtfyP//3o/3\n4Q4nnYwPf/LT/NmLXvSi3ns6ovbZwLa8eQcu2PdGnHjMHYeNP9E+64j82WC1I4Z6DcZ/6mB59/Pu\nje//ZLgERDvbDABYwny4e9kQ+pHdr+x3Jg7q0cV2YixGn3LI+E9elCi3YQ2Jbbew2sezzn8E+Ud6\nf9PP3dl8ZcPbxhjB4QTfqddce9+mzpTRHKANaj8Txv+knZvw7EfcGw+/ez2ARY0m+bjxX8PELTYc\nGT1uHcf/uXe83egxbpYCZUsYLhUhgeHxDrLMf6qlmRx3WCfkP5tI+0zNcE0HA5iuvplyz7t3bcZx\n24f76mfTOP9VKpGxFuO/3oh0LLdh5Ou7d+/GF7/4xTVfdvCeJ3pgG4HO5whosIC/rdbzPxyacw5X\n3udOo8eRsRpNG1+L8WfkP4ysxRiMD7L73fUY/N4nrsU5E4z7aMvIf+yqfip9pdpk4zHVqK/huY8u\nPI+4CjjxvMFDZG+FtchbpyL/8eP+8oX3w2IkqB9YxjzsWR5oSao7rXvAqIp5/dsGsR+DhnvqmFpT\nWe9ph/lj74rVA/sxO0L73AZanuxc5qGvHRTtM4L812DYHnDXY/GVVz0UKxN072MtriQ+9N2L++CK\noQPXQrmQBzUZ+U+0Mmsx/mMT6vxfHD0HFdCbtuClY9ym7ZOOm/I8Z8Fj7BX7lbR4f9cdg6G972ib\n0LXY82bdrf+tY+SGaZ+JyH8D+u6bZfhmWM21ke2I8Vdtx5ZNwE3A1k0j0sMwJk1UbSrts8byDuth\n+AHAzTbjHvuuxg3YOmj8F56K440HmZdnaUJNpn2mtjXQPutx7QNIxr/ByLsD8MzVl+Ky8Bc4bb2D\n3CNtxx3uihetPgcnn/t4VHbh5RbXoCajNjngO7UdIu1z8JcdP/MNcQsG39waOrcpz80ty7dt83rb\n7t0t3M44cRfwPeDEHetp/POoGUP+txLvF7zDv2IMrQILP41eAIRvX7/JvPaA73pwtPuQ3nOYYPw/\nhbPw8dUz8de3cMD36K3LeNFLXoljtg0jyK2bUuxgLcqlyQH7yW3E+G8Q/TFcdNThi+1uRDjcffgs\nk6+3bWWGux2/fbQK7a3dbtu9u4UbB+vG+Pnqpuo9bVfeyeekC0fOmSfvBGS9no0A8mCAFMCC9iWd\n0D+iC8aS0Nbc1slgTm37Yt4la8xrgxjKUbqJFvl1Qv4AcPsdI4l8AO5z1+MAADs3jwek6VSjxn/r\ncdM2Y6F2K3HbowlwE4i9v/3EJ/DIy/83AMCHP/xhfOITnxg8fi2G/0c/+hHXKKLzP/KRj5z8/YNt\nR4y/bjQxxwzcWpD/6Y8EfulTwN0ePXxck6tQLkYWnnVubiI/T8h/SqLcPe+UDMIYGp3cuKLoLWv8\naZF3E4x/myW6K7OxEt9UNvyWdbq35fIHYU21o0bM5vYTDnmXrfVslJVLbbkheeuhLzraKxky/mUf\nprTS+N9S7Yjx14009mMUzFoCYc4Bx54+fhzJD9tpu3OtV6PYQV+NEmqrHPwcN/4v+Lm74IMvvC/u\nnJNretsD/wOw5xfGO0mI/xZG/n6JFuTxd7L3pJTBvX3TCLL2t47xZ89ywvh69NknAACOP2oNHu6k\ndmhG+FWvehVOP/10POhBD8KTn/xkvPa1r8X9739//Nqv/Rrud7/74XWvex3+6Z/+CZdccgn27NmD\n5z7lsXA3/QDeO1xxxRX4oz/6Iz5X2sglGfJfvPSR+JXnPB2nn346nvrUp/Jc+MAHPoDTTz8dF198\nMd7zvj8BkEo1X3311fit3/ot7N27Fx/96EdxxRVX4IUvfCEe8IAH4KUvfSmuv/56PPaxj8WePXtw\nz3veE1/4whcAAK94xSvw2te+lvtw1lln4dprr8XLXvYyfOMb38DevXvx4he/GEAqUPeEJzyh06f1\nbEc4f922JtcY24bzATakNdMNzXo2Ck6tLoYH19JK6l8zIckreIdTj52QRXvfF48fAwBEx93Cxv+4\nnSkEuOTH7/ktTz8fX/r2DeOBeHfrLGRMVU4YX8++751w2T3v2B+w/L9fBnznH6Zf+8BP0s/Zln5g\ndfu7Aw97de8pPv3pT+Pd7343Pve5z2E+n+Occ87BueeeCyAh54985CMAgEc96lG4/PLL8fSnPx2/\n+7u/i5e/9EV473vfO9i9r3zpC3jPX30Sl5x7Bi666CJ8/OMfx3nnnYdnPetZ+NCHPoRTTz0VT3pi\nqve/+6QT8NznPhdbt27lrN23vOUt+NrXvoYPfvCDCCHg+c9/Pu5xj3vgve99Lz70oQ/h8ssvx+c/\n//ne67/61a/GF7/4RT7mwx/+MD73uc/hS1/6Ek444QTuU1nH6FDbEeSv272fDzz6vwB3eej4sevd\nGJndsrTP9pUGZ91hO37rSWcPHnfJWUlIuHPzrYAXWAk1bjDffPl5eNVjzlyXy97n9ISAd20enyY7\nNs9w7zsfPX5Sv/6c/6TWTPcsnXO3OaXKxz72MTzmMY/Bpk2bsG3bNjzqUY/iv1E5ZwD45Cc/iac8\n5SkAUtlmKvk81M7aey6OO/4O8N5j7969uPbaa/GVr3wFp5xyCk477TQ453DZU588eI5LL72Ud6f7\n2Mc+xiWjH/jAB+KHP/yhqiU0rV1wwQU48cQTTZ/Wu9223vCt3WYrwDlPm3781tuv47VvHeTfBI8/\ne/59xo9bSsZjbDe0DWkT96kFgAfd7bh1uywFt9dV430rcf5s/NeDPhhA6NX2rc+ln8edJV7cGtsQ\n7UHlnGuNuPqmadDmEisxRhw4cICP2b5lE+50dKKBQgjM21v10TAA0H2o9dU5Z/oAAPv27escR225\nKAd9MLGEsXYE+R9se8k1wL/7+/U7HyOzWxb5T24U5B6TrG5E48l0C6tFdqTNcHDhc9fvnBug9pnU\nwtrySDamjV97964tXIhNt4svvhh/+qd/in379uHGG2/E+9///ur3733ve5uyzUSV7N69G5/5zGcA\nAO973/uwuiogaxY8tq7Y93H66afjmmuuwTe+8Q0AwO//wf/kv23btg0/+clPeu/hvve9L5eM/vCH\nP4yjjz4a27dvx+7du/HZz34WAPDZz34W11xzzaTzbVQ7gvwPtq1F4jalEfKfoCy5VRolL9390lvh\n4hSIv4UN19ZjgFeszV0fb/lelkeC4evd6P2dcr9b9rq6TXh9fQHz888/H49+9KNx9tln4453vCPO\nO+887NjRTct6/etfj2c+85l4zWteg2OOOQZvfetbAQDPetaz8JjHPAYXXHABLrnkkkFvAUjbQr7p\nTW/CIx7xCBx99NG4+KKL8MUffBNAiis84QlPwPve9z684Q1v6Hz3Fa94BZ7xjGdgz5492Lx5M972\ntrcBAH7+538eb3/727F3716cf/75uMtd7gIA2LVrFy666CKcddZZeNjDHoZHPOIR4w9qHZrbiCjy\nerTzzjvv/2/vzELkqKIw/P2EmbRmxKzKYLtMRCV5kDiIKMo8qCQmL1EQiS+OC0RcQEEfIoLoi6Cg\nD6IoEQUVMdGoKIpocCEvMXGi2YeYcR+NzjiuQ4jr8aFOazP2NmtVdZ8Pirp16k7P+fvcPl117+26\n1tfXV79is/D7Ybi3M1kV6fotaXtTmdEhmLNo5pPw8AF4/TZY82zjT+TMKl9sha0PwxVPz/yg75fb\n4PilDT/Supz+/n6WLKm/xm5FSt0+ncsm1XZGR0fp6Ojg8OHD9PT0sH79erq7uyf8euPm2z1w9IJk\nimtGqBQXSTvMrPaDq4gr/+zQfjRcuRGKtX6knzIdx6XzfxedAVe/ls7/nmpOPi/Z0uCkOj80nC4W\nnp4s9j7Ji4a1a9eyf/9+jhw5Qm9v78wmfkhmJDURkfyzxBkpzDIKgummfU6yTZLSqlrB1BADvkEQ\nBC1IJP8gCBoiq+ODrcpk4xHJPwiCuhQKBUZGRuILICOYGSMjIxQKE38ER/T5B0FQl2KxyODgIMPD\nw2m7EjiFQoFisTjhv4/kHwRBXdra2ujq6krbjWAKiW6fIAiCFiSSfxAEQQsSyT8IgqAFyezjHSQN\nA19M4iUWAt9PkTtpE1qySWjJLs2kZ7xaTjazRfUqZTb5TxZJfY083yIPhJZsElqySzPpmS4t0e0T\nBEHQgkTyD4IgaEGaOfmvT9uBKSS0ZJPQkl2aSc+0aGnaPv8gCIKgOs185R8EQRBUoemSv6RLJB2Q\nNCBpXdr+NIKkzyXtkbRTUp/b5kvaLOmg7+e5XZIecn27Jc3wihb/R9KTkoYk7S2zjdt/Sb1e/6Ck\n3gxpuVvS1x6fnZJWlZ27w7UckLSizJ56O5R0oqR3JfVL2ifpFrfnLjY1tOQuNpIKkrZL2uVa7nF7\nl6Rt/h5vlNTu9tl+PODnT6mnsSHMrGk2YBbwCbAYaAd2AUvT9qsBvz8HFo6x3Q+s8/I64D4vrwLe\nIFkR9VxgWwb87wG6gb0T9R+YD3zq+3lenpcRLXcDt1eou9Tb2Gygy9verKy0Q6AT6PbyMcDH7nPu\nYlNDS+5i4+9vh5fbgG3+fj8PrHH7Y8ANXr4ReMzLa4CNtTQ26kezXfmfAwyY2adm9juwAVidsk8T\nZTXwlJefAi4tsz9tCe8DcyV1puFgCTPbAvwwxjxe/1cAm83sBzP7EdgMzPjSZlW0VGM1sMHMfjOz\nz4ABkjaYiXZoZofM7EMv/wr0AyeQw9jU0FKNzMbG399RP2zzzYALgU1uHxuXUrw2ARdJEtU1NkSz\nJf8TgK/Kjgep3UCyggFvSdohaa3bjjezQ5A0fKC0gG5eNI7X/6zrutm7Qp4sdZOQIy3eVXAWyVVm\nrmMzRgvkMDaSZknaCQyRfJl+AvxkZn9W8Otfn/38z8ACJqml2ZJ/pRWi8zCd6Xwz6wZWAjdJ6qlR\nN68aS1TzP8u6HgVOBZYBh4AH3J4LLZI6gBeBW83sl1pVK9gypaeCllzGxsz+MrNlQJHkan1JpWq+\nnxYtzZb8B4ETy46LwDcp+dIwZvaN74eAl0kaw3el7hzfD3n1vGgcr/+Z1WVm3/mH9W/gcf67tc68\nFkltJMnyWTN7yc25jE0lLXmODYCZ/QS8R9LnP1dSaY2Vcr/+9dnPH0vSNTkpLc2W/D8ATvNR83aS\nwZFXU/apJpLmSDqmVAaWA3tJ/C7NqugFXvHyq8BVPjPjXODn0i18xhiv/28CyyXN81v35W5LnTFj\nKpeRxAcSLWt8NkYXcBqwnYy0Q+8XfgLoN7MHy07lLjbVtOQxNpIWSZrr5aOAi0nGMN4FLvdqY+NS\nitflwDuWjPhW09gYMznKPRMbyYyFj0n60O5M258G/F1MMmK/C9hX8pmkT+9t4KDv59t/MwUecX17\ngLMzoOE5klvuP0iuRq6biP/AtSSDVgPANRnS8oz7uts/cJ1l9e90LQeAlVlqh8AFJN0Au4Gdvq3K\nY2xqaMldbIAzgY/c573AXW5fTJK8B4AXgNluL/jxgJ9fXE9jI1v8wjcIgqAFabZunyAIgqABIvkH\nQRC0IJH8gyAIWpBI/kEQBC1IJP8gCIIWJJJ/EARBCxLJPwiCoAWJ5B8EQdCC/AOEuksvAoy6ZwAA\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ff7e39fcf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAD8CAYAAACfF6SlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzsvXu4ZVdVJ/qba+29zzlVlUogJBBA\nXhFswQdyIbR+Ii1qN3jvBbXbvtK31fuBzeUqXpRrq23f5uv20d0qLb5Q4doq2CIiovIUNQkkyCMv\nSKBCQpJKpV6nTp3Xfq33mnPeP+YYc461zzlr7VCnqpLKHt9XX53HPus555i/8Ru/Maay1mJhC1vY\nwhb22LLoYl/Awha2sIUt7MLbwvkvbGELW9hj0BbOf2ELW9jCHoO2cP4LW9jCFvYYtIXzX9jCFraw\nx6AtnP/CFrawhT0GbeH8F7awhS3sMWgL57+whS1sYY9BWzj/hS1sYQt7DFrvYl/AXvaEJzzBPuMZ\nz7jYl7GwhS1sYY8qu/322zestVd1fe4R6/yf8Yxn4LbbbrvYl7GwhS1sYY8qU0o9NM/nFrTPwha2\nsIU9Bm3h/Be2sIUt7DFoC+e/sIUtbGGPQVs4/4UtbGELewzawvkvbGELW9hj0BbOf2ELW9jCHoO2\ncP4LW9jCFvYYtH1x/kqplyul7lVK3a+U+tldfv96pdQXlFKfV0p9Uin13P0478IWtrBLw/5uY4ST\neXmxL+OcTU8mF/sS5rZzdv5KqRjA2wC8AsBzAbx6F+f+bmvt11trnw/gVwD82rmed2ELW9ilYz/4\nhQfx0s/ec7Ev45xs+P6/xJdfdB2Ko0cv9qXMZfuB/K8DcL+19qi1tgTwHgCvkh+w1o7FtwcBLHaN\nX9jCFgYAyKsaAJAYc5Gv5Nxs/OEPAwCqEycu8pXMZ/vR3uEpAOTdngTw4tkPKaV+DMCbAAwAvGwf\nzruwhS3sErDtrL7Yl7AvtnpVDw/91LNwVVng0MW+mDlsP5C/2uVnO5C9tfZt1tprAfwMgP931wMp\n9Tql1G1KqdvW19f34dIWtrCFPdJtlCQX+xL2xdZf/Hlc+ax78MDao4O+2g/nfxLAV4nvnwrgdMvn\n3wPge3b7hbX2HdbaF1prX3jVVZ1N6Ra2sIXto33ulnvx5+/8yAU/7+ba2gU/5/kwSzB4bXP74l7I\nnLYfzv9WAM9WSj1TKTUA8AMAPiA/oJR6tvj2fwZw3z6cd2ELW9g+2o2f/A2M6j+44OedJI8ehUyb\n5WoJf43vgy7yi30pc9k5c/7W2lop9QYAHwMQA/gDa+0RpdTPA7jNWvsBAG9QSn0ngArANoAfPtfz\nLuyRZ5MHN7Fxcg3PfMlCyftotG98/scAAFVVo9+/cN3eJ9kYiB/9kf5fLr8KN6iX4eAVN+J7L/bF\nzGH78oattR8B8JGZn71ZfP3G/TjPwh7Z9qfv/wWYg2fx+pe8+2JfyqPa3vrWt+IFL3gBXvrSl17Q\n8xpEqNDDmc01fNWTnnLBzjvNp8DBR7/zL9QAAFDG8UW+kvlsUeH7GLXCGPyP05swdv9Ut9d+0wfx\n7Od8FnVV7dsxLxW7aWuCjXI+VctoNMKNN954nq9op/0+Xo/XqD/FZLh5Qc+bF+kFPd/5sghOqqov\n8nXMawvnD+DLSY47J5fGAJzXfv3YGn7q3hP44Ppw34+dbj06El4XyqZFhX955wP4gVvu7fysuYha\n90+o7wAAbCUXdi6U5fSCnu98mVEu48uLwCPdFs4fwLfdcg/+2W1fvijnvvXMrfjixhfn+qy2FmeL\n/UHVG1RYM6z2H6dsr67u+zEfzfalzzl9w/1JdyKwnjM6OJ+WJqMLer6yKi7o+c6XWXKnkX10YP9L\n2vlrrXHTTTehLC9sz5BEa7zz1MZclMprPvYavPrDr57ruP/mxtvwDZ86gvXi3O+HizP2s9TaIEKO\nZQy3H93Of62ocMdo/7Tn9569HwDQL7POz9ZFiSc/+R4cPHRhqRdp+QXW3Zf24i94+2EL5P8Isttv\nvgU33HADbrr+Exf0vG85uoqf+fJJfHRjfxHUZygcv2/z3I8b0UDdT87/9/F6vFb9CdLJ3rSPtRan\n/p+fwvTmT+7beQHgviTft8Zg//S2e/Hdd9wHu0/PZkzXZedwCtk4w7VffSte8IL90duvlxXunnYv\nOtLyDqniu09vYnUfAAhbvc8s+XpZYVxfePSt4RK9yi6c/0W36VGHntLTFzaM/eQ9Dul99mh3OcPT\nx6/BNcl8wjBFzmg4Pvcw+Xwgf+aMxy2Rlq0q3PGlHo686Rf28czAS265By/89N37cqw1ol5ysz9P\nZzg8CQCwy90qkOnWFmrEMPs0NZ//qSN42a3duQZpZb03tTisarzp3hP457fvX6lOvVuPgHOwr/+H\nI3jZrRe+ytYyoHqUeNULJ+a9CGYqtwLPO4W1tYjVPozEszlwCDjx5QeBF7+o9aO3fd23z31YHlxl\nde5hMo/PugPdfn6c4pbRFK/7qqvnPnbaovapxilueMVL8MTj37SzAdQjzApjsBK3z2Q9LQEDxIcH\ne34mhntfJu4eW+PhGn5YvRfX2i/ju1o+Z62FtRWiaO/zAoD+CtavooWDP7vlejSeSh5eNNFm9Xmg\nSU7mF15xZghS2f3wIRfAHiVr1Fdm65sjHDy0iTOr81UQFvuE9A4uPwQAiLN95r4jd32j7TPnfCge\nn133/BP3HMeb7z+NVM8/QYsW5Hjn7TfhT7/uKfjD73rq3MfrsvxhXNvDsUx3L7J3vee3cMsftUcx\nmmiNedD8ZHwWAPCAek7r5951+zvxnI9/BuvpVucxH67V9d73vf7gKQChlUGbfe7s5+aizuqL4IVG\nVY0n3fh5fHQf1W6a3q/ucP7TT96B9IsXv//PJe38B4duxwte8BEcPnj7XJ8v9klmt3zIoSJ7YH8T\nzUvLLhE37VBj1PUEdk7FQdbhOO8hhcrDcf5Vi/M/NXQL4ri3Mvfxumx4nhQykzlUKFvP+h2kX9de\n1FY/DHItT+Zz5r87fBym6jCuv/4f5vp81bHIS4lpafYeO6dOHXGfj9qPd8PxG/BDH/0hvO++93Ve\nmyYvtB8qGT1nnub+1L3btx7bv75CRsX0f7vzH34owcbb94eiPBe7pJ1/fNh1mo4G8yknxtn+9OSI\nCelVqt/6OfswIw0OJ/N8b7SidYpP3PR8HD36663HSmu3MLVN9MbndfvnJMJrQ44pJROt6h56WT0f\ntbCxT/LXWZvW+yNBNGD6sRsul9m48zMAUJOjWV07OdfnO99fHYBK3TImxpkTHXRFMScmbu4dHXZv\nbFITHRbvQ+I3nxPA8af0Pma9+P2aqP09/7sXfQl/+I0b+3ber9QuaedvFU26eWJUAKPJ/iSGl+h/\n1cXHPsxIg9UEbZxsUTja4NTpP2091l1nXNh579b9c5077bhWW4ffVy0cbl7NFw2dmJzAdX9yHf7q\n/r/q/OxGOt+ivbX5ID78V9+LJJkv1GdH12ZDXIGTaKewDI2/eZx/Vc0ns1T0jKd6vgKpSd3+3Osi\nnLduASU5RXVd99JTMZ628axWIMCmo/mdfxdgyudMcpQ0nut9VDzwgmg6gM3fPf46/O611+3fib9C\nu6SdP6/vyszn/LeH++P8IzqfjjqShQ9TjsYTrmr5O2PcwmA7nHVEOvZsbb5q3GlHywZdBJTehhyL\nOe/52OgYAOCjD36087N/d/SOuY55y8d/FMuH78ItH/3Pc31+tN0+Hqy1+En8Dn5G/Ubr5zQNv3mc\nf13NV13LWvJyzhk8rdsXyDIL46BqoU4KQ86/w8E98Lkxbn/Bf8LJI930Xk3zJO6gfe7++/+IG274\nmtYFYF7kz05/P6XODM7a3E1dPnI6fl7Szl/FhDrMfKKm0XY7IkyrFKOie4Ew1j3WuqPBU54/PFqB\nkUXdoiOuS+fUdd4+keIBIb18PpphVLUP2joJ1Fob71rOOdm00fiW4/8IUdXtMP97NV9TsLIAJjiE\n9bPzCQC2O3rclOUWSuXivLY8RxcH3PisnS8yimgMVHPQZwCQdjiddBS24GirRyjovF1a9nunlwMA\nTkTdDeLKnpsnXcVRq9EfA5FGOdqbMplXtBGQf/vn70ty/Maxtc7EtTFlQP4toK+e7n+C/iu1S9r5\nI9K4B18Lo/Z+cfKlTjoSqa94/yvwT/7sn3Se1lg3mKuow/k/zIZWPLh0y8RLRm4HtKKDyzeUjzBz\nRkVpB/+dDo/7r+sWmq2ck2NdveU+/MM3/hgOfe7xc31+Hvvc4Ll4vXonjs3ZPngybh8P+TQ4zLwl\nX2QfBvKvMF/yWtFzrOZcWJJp+4I32jzmvzYt46uN0mtY393Hgd4cVc2EzeZ5PgCQrB/b83cS+beh\n+oTGc2nan/e//dID+C8PruJ4RwFhXabB+bfcx3jjbOtxLqRd0s7/6NJT8AvqF3H9E/fW2suhXHQ0\ntLr2+LX41lPf2nle7vHR6fzzwNfO09ArIP+9B/VkfRUW7QMQAGoq8WCFQpelun3wT9YeEsfe+/rm\nVb7cuX0AG5ddgc9c+5LOzx62zkk/zrYj9buXvxoAcGxlPuefTdv59Ozsl/zX4+ne9BlL/+aifeL5\nng8fS88ZVEy22yO8yVZYyNqcJo+CLpQ+uMw9u0OXdedXqt58+vgaMaY4hPTU8T0/I2W/bfPkvuGD\nAIDtjsj3c9sOTJ3eeqj1c9X4bKB9WpD/xvojZ9eyS9r5bwzcNsqnl/ee7FICV3WExs8qnohrbDeH\nyROzjNvVPplIKFYdYfRdd90VkH+LAx1truFfq7/AX8Xf13q8WjnnbzuUCWzJtH0SjzdC7UHb9dVz\nItVIu2eztNTNkXLyU3fWLFr6/Hx5hzJvP/fW6dCQb9oSJVj/f/e9F/F81+ad/xyFYwAw7aA0J9Ow\ncLYtP8zCqY5FvEdOuO4AQABQxDQWO57Pe/CD+D/VO7G2sfcin4pGhW3JXM5rdLXcWE7d8U4fa9fl\nl+un5hh/wMb2xevZNGv74vyVUi9XSt2rlLpfKfWzu/z+TUqpu5VSdymlrldKPX0/zttm2SgBIvfi\n2lBKJRB30ZEUe9F178eL//FfdPN/nJiN2gdDVgQqpaug6IYb/zpM+JaJtzlx4f0H++0tI+o5klPS\npsN2xJKMBOffMom7CmDYejEh6QPd1FiBZQAhmtnbyPm30IDSqg5l0qn1df/1tGUrQub855G3bi/N\nlwcyvpXAfM9zMml3OolQ+7Q9nZrO1+X8YwJV87zvnPImXc7/o+p/BQCcbqkuHgnlV2uEXLASsOM+\nSD20sbre+rnx+sm5Er5bySOnffU5O3+lVAzgbQBeAeC5AF6tlJrdx+9zAF5orf0GAO8D8Cvnet4u\nG21sI+q7JJxqcf6ZQHe6JWkHAL2ec9BJ2S7HY463k/bJwnHSjnNffc1NHlm0heXbc3YwZeQ/r/NI\nWpq1AcBIhM9tVMS8fVx44uo5aCmvr+4YzhE5rHkXPN3BB5+sw2KTtjn/OZ8xAPTmdP6B9pnv2Hna\nvohKKWgbFp7X+WsSPcxD44/U5XTe+dzRer73vYwEVdfm/I+tuUhVdYCuXuyexvakHRiunj2OCi7S\nb6Ovpi3XfqFtP5D/dQDut9YetdaWAN4D4FXyA9baG621fNefATqE0ftgGxunEfUc8m8bqFNBZ1Rz\nlPMDwGirPWPPZ+tC/rmgfbIO52/rvkcWbWhlTL/rUmPoOasR2dKOzpBjFZxWG/KvO+SvbDyBdAda\nttbO7fxBiL+ac5u9tsQ6ANwzuNJ/nbZM6oej9uktz7d4e+c/5/PMO0DBVBynVapIn2sDVEB4F11o\n3lqLEa6Y67NsE7X3ubcnAYS01StcNnKc/4EOeenKQfdeJx0S3NFk7J1/W74tEfN8v7rGfqW2H87/\nKQBOiO9P0s/2stcC2FW8rZR6nVLqNqXUbevr7WFWl02TE2FzhZaBOhQcXNWhkPkEvh0346XYfLC9\nS6JvwNZR4ZsL2meatzvXKH2cp2rQQlskar6CmcqHqHM6j6wdkebCn9qWxXZeZ8XPsIvKqcpK0GFd\nTv3hOv/2ybnVO+S/LlraID+cRl/6YSZ8531/bZ06AWDaC2O1zQkz8o86kL+PdjootrrOPW3XJVJg\ny1qe51hEYG3I39LjiDrOGSk3j4qOsVBlJWpG/i2vJBfRpJ2jAO582n509dzt6e36pJRS/xrACwHs\nujO1tfYdAN4BAC984QvPaVlMx2dQHu7TBbYkSEdbAB4HoHuyv0O9AQDwnSfbewV5zr/D+VdV4cuB\n044e6rEGLKH1tqtMKdrocv6M/LucsbIaVsWoOtoDlMJptSFdpim6IpN5kX82lRK79s8y1VXP6TC7\n6KE0Dsn/omWjloel858zgRs05fMdt+rozZQKcUJbQXyI3DqcP+ckOu69ysbIyfnbObFom7x1mqXA\ngcvc51oUdEqt0P/t52LfUXcsElWpUYTa/j0/l4vHVtc1Bv12H3E+bT+Q/0kAXyW+fyqA07MfUkp9\nJ4B/D+CV1trzvm9bsbnmwzCJ/E9PT+Pnbv45pBTGjcaCq55Tw5zO0D43n7wZt5651X/vkX/U4fzL\n8BjGLZwxAEDNFy7yJO6hHel5zr9j9PNv645HU/bCUGp1HnF3NOaui/7vGKIS+VsVtT4bXozn5eA7\nHZdYOPPy3Iu8rLVzX9vDXcjaCgMBII2Ww3W0Rm7zUWxmzsV7vLmBmt5LW8RhReTSNrKTKizCRUtV\netd1sXHg0qWqKoxCpVw7F/m+rbUwAu2X4jD70Zr9XGw/nP+tAJ6tlHqmUmoA4AcAfEB+QCn1TQDe\nDuf4L0iVQzZOUMG9DOlofvXWX8UHj34Qd5x1LQGyNCRdzZwa9CJtZux/9PofxWs+9hr/vXf+aHf+\nMhRP066eLuHadIuDyMj5L3VUinJjsK6EoZdRdvRHKqLdkeORI2/C7Xf8K3Fe5ozbnzWjwC7HWedF\nw2m0ubjKL3h7D3u5eHQhfy0S+m09bOZ16FrrXSOxUpf48et/HLevhYiTKYa2e9GCxuxqYCadf9sz\nZ+lmF8U2b+S2teWqdZdt1ur8syTQwG0LXi7m1LilsM1LjudN/nfs65DJ8S9+/sADv4qPfyLoX0ox\nFpKOuqLzbefs/K21NYA3APgYgC8BeK+19ohS6ueVUq+kj/0qgEMA/lwp9Xml1Af2ONy+mdYaJTl/\n6YxUGeNZm89HUroHn0q1z5wDoZypdrWqDxMdFN+7/yvVb0WitQ4DNUvbJWBdUQRbGrvQs49251/N\n4TyAMDe6HGEpktvyls+s/TWGw8/675nW6FSL0GXtRgWkIvlWFimsihDTPrBt1B07/7bFU/YF0x2z\noxYOsGxz/jNIcM9z7+H8Hxo/hI+f/Dj+223/TZyb76WllYBAnF3VA1kskX/L84mYYmt3/rzgdam1\nUsp1DVC2Rm6nNk75r+uW9ycr29t6MzHo6YpgePe8tsItAMjl+Bfv+6Hjb4e1GoZ6IhXiOMPh/u0l\n8JXYvuj8rbUfsdY+x1p7rbX2l+hnb7bWfoC+/k5r7ROttc+nf69sP+I+XBP0rtn3Jx17Iv5V/0pM\nj9PLqKVKZW+TFbjFTC/zyeN/BJtP/T3UpBbyDdjUAHlLIzOpLpp2dJAs9kAWs5b2mD/toCzmQMGA\nQP4dCFw6/3mQYyfy97RP81hnkjO47t0vxvu+7PrEl0SdcY6jrakjq69aHaZwPm2JO6BZwCSVQUfu\n/ml87vM/4r+Xz6Pt+rTWDWfJjrDMa3zvkTdgcPpx/ncVumm74mE4f6aRgCZYuuWO1+PTt/7v4byK\nI7K4dSHj99aF/Kus+f72itzuPxMIg7bFW9Iq29tOnmyNwa2v+hZ88W2hoZ+O5ru+8PkO5N9rn5/G\nOJAp1W6T0SXg/B+JFqna0z7SfzznwOdRPu929LZcdWYleME2ykAO9KLffL3FwW8BAJwhrbuckNvZ\n3oiwFknUsiPh+9Dyk8V1tiS84gMA2hFXbezcG0/wb9smHNBUNknk80f4EfwUftN/z5Ooa3EKCcPm\nEL1368vYftIv4ZeOOmdQUE8dv1Viy6ISHOaczr/j2UjqoxYL+Zkzf4GtrRt3PU5bx0xjjKdzgDAe\nx6tn8NKX/wq+cxrURQxs2pxXKcZX1/uTY186/8nw75BOPiOOE87Xei/sXDsihJKq6iN2/nsc8qGh\nkHCKe3bbWYY/KsW4Sqbub6Znj2L8xjVsHf3jHffRWRtCx667aJ84tG+X42uMw/gSngtNe1OUQmnW\nRktdCLtknb9VgfaRzvKOy5+Kf6t+C/dN3O8KOUFa5kdjgPV2H6HHqDGcdGyb472duhbnLor2HPjx\n5WvCtYjr/JVbfwVvvOGN/nvv/FuEXHLHsk4dvd+gov1z5R6c/9+pV2BVPcVHTvWck85Xxc4sEqvZ\nBHrwNKwuuQW3qtj5u+O3NXXkhG/bPUuH1hXtNNByy4kl599GSxljUKil8D19tB6ewD34Wlz+jM+5\nY5gamu+l5b1I/ruzGEz8vg1cSOTa1j5hbuRPkRvn5Xjx3thYxcf/x/Nx5K7rAQBDUbkr+fdfu/3X\n8A3v+oYQJYlnnVI0vbnqWjMkL9057rtoqaCqan9+DeQvPvrL+A/4RfULSHIXhUiZcZpd3GrfS9b5\nKxWkVxJ53dN7GgDgGCEnqYJoe8GNbe76u4/6NdqFSZ5vmLYgf3HurgKzIhogJnGyROt/8sV346Zj\nN/vvp5R7aENcmXBUnU7Y70va/jlJS+2WHyi0m+S1n3Q96BaePNA+zfOOZySL3JLD757WIkmdx/nX\nsitkx4JXK0n7hGf6TrwWb8Jvh+NgPuRfl4WQCwZHeOLUBn5B/SJ+65BLnEun0Ra5ZTKq7Zjp8hql\n87oZL8X78f3hGsU9t+nog9qn3blWNAb4/dX0fu/79K9CP3mCM/f/DABgVImGbeK9fPTIu/CtvSWM\nSzf3pAyUay+m227r0EjM23mRv2+m2FGtX8a7c/4nSAh5krp5VuJzSTbfTnXny/ZD5//INGWRwaFg\nOUFYX87NveRkbEM8hXA6pXhqZR4m2NbpM8DTv7FBPIxa6BzJE3fJvgwU+qig0W/QWD9755twsH/A\nf58px/lrOE5W0b1/ee3jePqV12Gpd6CB/Lton3mRT7OmYedn0zLBSn+lgVTrqkTc230Imj0kheO0\nGSHVVQ30pPOvAey+g1pBUrw25y8Thp1qH3Ftkm76W/Xd7trKKXqDQ43meW0OU1elL3gCQn5gnLux\n8UDsupIm49DPvo3CygvRsqHjPUuHJb/+PfV/A3D9W4BmpNFaRMXOf+b9GWPwui98Cd9zzVPwv1x9\nhU9KR9YAipPUPWyNLZYPAql2evyxSMDI9/cz1+SIelNMizEuX7q80VKloKhiuHkCuBIQgdrcyN9X\nwneMfxlZNaNV9/UmqZpKcX1ped4V7612ySJ/wIriEeH86X9GQrLFcGvyTDhnifyn2wGFDU9s0nHC\nYx0Ve4d2kkrSM9XFx8fH8SCVoAMOjbGDk1Nu9WmfxoNP/Zj/nptk1ehBE8I/dvxTOHHktfjL9/9L\ndy8C+bdx78Za34ysy3mUHch/ShuTSwSVZXvrsK2nfSLUYo/e8Z0hSWasEbSBeza56FHz2x/7G9xx\nLJScMA3Y6vxFBNaV5JPvebd80cb6STqfQKNtkckM8ufxkXnA4v4fbYYme233kglk2Yn8Je2zy7vW\npJ9vIP8WwLKXc/3TB67Hh7Yq/MiRY+4YJIjgsc2qqXq8hFvxYpQE4NIoQp/ky/K9RNRva3vLqYGq\nKPYAr6R3OZ2OMcFlSFUoyuNjzC5OsxaQf/vn5DXJyIn/fotyFpL2qefc0vR82SXr/C0sJjgMoDmY\nYxoYPBnkpG1b3UvRG6US43kk2kNMxrSFovi7abp3Rl8ip3qGznjjjW/EK//qlR4ZGRUFXlvcz03P\nfx5+7etfi5L67ZeMbhH7rqFn7rwLAHBV7BwwI//Y1o1jFcUaRuM7/fdSmdKV/Gxy/juH1eamO7d0\nVkmLwon7AxlEqDbFM+wHx5eUCTRNcN4CMKPd0bKywtf2fwxH7vjfwjWSY211mJIq6ULLkirZpYjq\n1GlHN8hnVxZ7O8yqzDHFZf573uO5VNyK2v2/3nD+LYBFOP+u99e4l11+P91y55TOP2+hLdgBzj7r\nI6Nmd1gGKLwzmab3+EV1GL+ufhofPvAd7lyRQh8lYls3Er7H8Ez8Nn4Cq0fvdtcXRVhCTsd2zzpL\ncrxe/RF+LPr9cF4GNfPSnh20Dx+vb8vms6Sfj6aujkeq4vKOdjLn2y5Z55/HA6zCKWRsg/bh/i5c\nIRn+pm2yyy0Xa1HNOpKtjMt6x/kyse3j+ugM3nzjb/j8gRFLz2wI/cXqiRg94Sdw1/oX3DHhkmKu\n3UI4/mfUt6JQy8jSMay1Hjlq1cNk5NDG9jbzje58GZ1/CUVDR3/bZ/8Fbrvt+2AMyyZFVNQR9krN\n+271YBt0LdIZTCZ7qx34Hg0ijFaDzC8XbSRG2QQVIX1GjhntJTycuOf+5Csc8rfGBOTflg8RDdo6\n6tpgoXx9wW4Oc3XNnVtGCGm6t8Osq8KPWSDkgXg54svZEntNt9E+mWgf3OX8G7UIu3x0fcMlLKXz\nT1q2IeXrmn3WiWl+X5P+nYENA5YJIenV+In+miIY9FA3UPZf4vvxafUS3LURnOsy3DF4ITGU+NaC\nmvTOX0hWz4xyvO/2k7vfR1cUSL/vodr1WSdUTySdv74EKnwfkbY5uMyvuo0KUMVbLO58qa3OPwkV\nuLUo9R6PQ6vjkvYPkMep0uDg/t0n34534KV48yff6z4nC4pm3MfkytejPPA/4f6p4wqtUlAwiGB3\nHVxnz6wiN46mWbbOwYy2CelPNui63STgDWwGKBoUTV47Z5U95BrXNZx/lypoF+chaa1N2uxE0j7T\nyd5RkUeOiLC9uup/LlHfeDIJyJ+cR07SwXS8gXfjh3AbrnPfl1NBYbU4TNFgb557jlr06RvDbTpO\neDbTZO9K7rooMMbl/vuSHGHup6l7nsOpWKDa+sjk89M+cvR5pZV4f0PSpDecf8tOZ3slfJNRc8Hg\nLSNZ7aN5QyXFVBcXWVlEsIiO8kRCAAAgAElEQVRRN6lDOCqHnWsdxR75M8iydqeTlSCEVUtv+dg9\n+Pd/fhtObofn63NeXbJf+n0f1a6f5XofmZOo59xU6HzZJev8udIVaE4Qv32hL/IIf9P2gksxkSoh\nNZuICZD3zY7zabFJxjhyIf3GSYdkZdSxl8z09Nq6P6aCRdSIF4Ktn17zSpUBIZ/hyDl/q91k4E1M\nSu/8y10raO//opPX1Q3nv/v1hd/vTHhZGyiU6cQ9J+k80jmch0GM8XBd/FzQRknqOWOmDXJC1pPV\nVXxYvQpvVU4tMtwWRULiGFVa4MEjYZcmWWndFe1YKEHFkZMSyfSUEq7y2aQtzl9XpacqgbAQVTPX\nMS3nS+TKneK67sWoCBEhZZ+sFRXoo7Fz/tKZJ5O297c78jd3Nx0xjzF+fynVbbCckyN1qywUDGI0\nI1+O+MZ0nkr1Au3DC4dwspoa8DUL9IgNOP5x/OQz3otT6wGU6DkFDwxK+qh2XZC5yZxs817PsXXr\n+bRL1vnvhehnS/xl8UurZroIzl8OnFQkdKsBDVTx8ssqqH36RKdwtV8Dbe0hnJie3PD3oGAdEtpl\nwg+3h6hpQ/g+EQV+025yworQFCuXBih3dR5njzk9eSk4ya7tHuXle9ReBueT86QTjneatThC39I5\nRioiBJl4m6YTX1zFTiAn2mbrbLOF1PoZuc1keH+fetvv4fTNb8fRh9wCkKbzySgBp8Di4jJeJyvh\nMAuzU5qb5XtTXVVeIMUBHLTuGni/By4wYhSc1VKR1IL8q0J8rvVWaCHj47oP56L1yZTGUmPxTvbe\n/9br/Gecf3WNe16KHB9z/nzugjad4cSo34AnCuBH5jn4+CX9rIp6WCLwY3n/BjGtEwIBchFjF/yy\nr/4zPPs5n8X66v3hd3sIHt7yqU/jp2/9fLiOSDr/nVby+FCxX2Q56rHWYvX6+1BsXdheP5es8+dB\nqqxpSDh9Yyp+qY0sfQvyF5JNmbEvRERQkwqogYJFoU0P7NBoAZKDeI/+L5wgZM5TzQx+tmmWos7c\nBO1ZTnSRc1UV7sLzcSa6GgCQUgdKh/x3Hms0dki7Mns7mf/vpqO443igvKwK/DdPmCIJTrusmHcV\nCcOiLWHIkVkfpYie5AKdplOf1OOEL6t/pmnTya6J/SEaeYenfQj5cz6Ae265yR1ToOV5CuB8WwJ6\nPJlY0AoWF4hnPNvD6f1r29igXFFd5TAq9os3SxWZomSxQk7jI7a7o0y2Mg8RwuzY/q+f/s/4s3v+\nrPF73yKDPjsVlCbnUmoVe9VN1rIHxV5dPXuXUcuFKEJpjJc7M/IviPap42YbkEbkK+4l9Dhy30vk\nz/LbvB+kv8PN1R3XxTvjrRxw19b7/IfD7/agfd6WG7xrCpykZ6wpcopgdvUjHBnuFpmcfXANb7/5\nT/Dnv/7OHX93Pu2Sdf6NlVgOlpk+9k3k3yb1DCiqEoLhXPQG4lxWg/YR/VV6BDFqv2G1rCYN55qM\nQ8vonJPIYvDvNt+zIkdN6LpHkzhlNUak8cvqP+Dnlt3umROqRO6j3FXtQKdEUe/tPP74b/4BP/y7\nN4R7R7RDiro9DPdRcxJZOH8u7d/NGiokLZLt0vlPNn3Izpwx9/pJiiaK2hy5e46sbtxzfJlTn6Qn\nvwSgud3hPNp4pn34nUvnXivrP8cmHeb9ky386N0P4f86ctT9jugcXrxzuge+Z84vVHSupZnIbXzb\naZx4b1Brya6xs5z/6nvux5/89d+H30PsAUGH3N4W45DGf42epxWLFrWWpH20qDcobahjSOrSk5jc\nRqGkaIMBlm+sRuAnhm7WTZDzLyk6qlWMAUr/NwCQiVoSHpMyImHkn2EFf4h/g+0sLHphX97mWMiU\nK6b8Eu1wp1WEHmqoPXJyvBDVqocluj52/l+880580ws+hOzJ/7Dj786nXbLOn538rIPztA/TChL5\nt6IogfyFaqAUYT4vHlIFIjlgbanCNN45oOTXJ08c819ng8wfk2kfv3OV0KQXVY2K+9wQCmYUpeNm\nYmkyclTSLPLXiPBu/BDWD14FIFA1s9dX1gYvGzyAf770Bf8zC1GHQJ/d2gzUS0XITtIGZYvOWU6g\nXHRwl+8rTyewXupJnCodU1IeALBNC+Ey8iZyrF1uSBm3OBSi8Ga2wvcLN/wt1h8StRcICV+muhIh\n/a0jdlzhOIWIdm457ja0u5P2lGBnzcg/p/qGamYPhIrONZhRa73vr9+P/373X6LK3DOQVePyeeq6\nxodf8Xrcct2PIWeJsUD+fC9bm6GYjK+tVj3vXNt2L+NoxyBCMQrqpEoHrX1aF+DpwYtoQQuFd/7+\n+jnytUEGbIwviuPPy2iM76PoBeS/TcKDSlZnU+3FXfb5+Hv1cnzwaS8K98GikRmHfsi6yHK14Ig2\nQkzOf7diUfY3jciEPjYdPoRDh7bxjOd8ZsffnU+7hJ2/u7XBDAdXe+ffDOdiW7X29q4ECpZNzCqh\nJJDH7BEXrMU2drzwsFRU8rCSytlYD06Tq4mNUlC2GfbmgtoojfYadz53TVFJOgjJbwCYjAXyF47p\nQVyLD6tX4cPP/C73d9PA6TYQZlqg38+glKSFoh2OcCgkibX/X7ZB3tv5NxYbkbBrOP+y8Mifnb8m\n55/NaKhT4smXkTUcpq4HOI6nw9DG6UUjmdq8pr99+2/iXT/94+H3ItrhsD7dCqiRWw83ck5icdmk\n/ERKJ2IHy8ifqcbZTqicAJ7N2ZinfwLf9IIP4egdjrOWzl8i/+lwiOmSc4gPUFdNg8hTL+zoRiLX\nwglLh/zJQbdsluK5csTINmUCVSh18sxvoBTNLN684DGyZ/AT20Cr5EXi1T6cF3Fzr0nFSdpnNHVj\nUkagPE8S65LtZw9eEe6Ddf6ymtsY3zJ9i963jtxYUDbE842W2lxUqkJOgmFhkQzxB3gd3oKfw4W0\nS9b5e9rHVg0H51sZc28Pr8+tWzP6cqBL2kfu/tVA/j4RKJ0/DaS4ufAAzcKo0SiE26XY5SiCJamn\n+91kLBKhRvuKTo+CqVpy0g+hdl0UmBDSHIiCFGutLzDaWHatgxO50Y3sVzSc4Lpvfj+e9/XXh+tH\nQG88OSciIchOWqsYS5ZC+5Z21w3nr3YusABQVtr3R/K0DznQcqboimsblpE1jnFWXYV/p34N73/K\nt7lrkpGckotEhadc8614/GXPEvesfJTFz3EoKDsd73IvIiK55xipvjhpSclPXrxZLMColnvos9R4\nYJvO/5nPugOHDm3jgS84+kCLKj05B1ZPPuS/PkVRgozc+JjjLICLymjAWmgEWoUjt+1jZ/GW//TL\nOHnPMXG+gPzH62Kf7KiZ8+G35LtnkryV9fBedqp2JnxH0yFSqgDmxcJCBdUS3XIumq4NidaTTflK\nWoRZaRWJDeID5y9UZnmg9s6ucwJZ0j7us4l41zw+ahUH588LQjXF9eqf4U71Amh94ap+98X5K6Ve\nrpS6Vyl1v1LqZ3f5/bcppe5QStVKqX+xH+fssr2kV7Pb3+lYIbaVS9S00T7CKXAVLRBCcKA5UEPy\nTF5T7M/pPh9+J/MNDcRNk4V1/kpc58a6cDTWYkINv9ghccuIpB+QfzbeRMa5AVuH8NwUGM8MfinF\nlGHvaH0Tv4T/iHde8YON3/N5+TlM5EY5HvnEnjOurFATWY2qEq0bJDUjOV7Zu6XWnlbzCV/drIpl\ny+n7ZeQN5L/VcwvdFw492/3dHs3miskIb/6nL8Eff/t3NK7R7xLHC3Iqoh1+z3L8iYgkqprTj9sR\n9C0ngKvGPTP6ZEc32CNnk40ecH9nZWQWfr+2etx/fZZoKCf1tFA2jK+J6DRbAaiLDFrQPkw7fupv\nbsF6T+NdHwsNBiVinsoFUeZs8twrXvz7o8W7oB3pvNQSoDqXEPmub5z13DsjeQuFyIQ8AQDkgvZJ\naMGq0fOLBOeeuCmiFYWEu3H+k8nQF1OORoT8FSF/kcmbVnL8K8BaVKrvE+asRtIib3h6GGjF823n\n7PyVUjFc36dXAHgugFcrpZ4787HjAP4PAO8+1/PNazwYerZultfP9HdxK7Z7aW1yOMmvV5CVgrt3\nCmT01kg20yTm//fi/BsNn2JG/m4/UacmcL/a3g6cbG2t56sZ+bMMciIav402T6MwlFg0xjtCY3JM\nCPn3uGAq2T35mWyewD3qebhVfXP4/S5ca17ulBpK5Cgd4S1f+K94383fjbpO6H4FVdJYQEUUZ61v\nqxBzYpCcRzXzLlkKuGyLhjOexK5H/oB42HqPpndbRx/EeOUg7n7y0/3PGjp/OqZsWRFoH1FQJBYX\nK1tiWOupFaZ9ONqs/HhxO10x8h2YJrDJ7DLehjfi9GFC0YLwlONwcz20WNiqZE7JEHKlZ9Nod25Q\nkK6/T9JhHl+jreP40De/CL/5DV/vI11Zp5Elshe/oH3S3CdCWdLJVBW3CwnXTZGvNf55nlkLxX+y\nBThHER75i1773KOrUiFxzfLgKS0kskOnR/7CVU5HI98qZEq7yjHyj6z113J2EiIeoxSsrlCh77dY\n5ftIeuHdrJ5+ABfK9gP5XwfgfmvtUWttCeA9AF4lP2CtPWatvQuA2e0A58P4BfRQNyY7N3fyzj9y\nTiuCaagIqmqK62+4Fvd83rXmlRRFqXZ3/mEAhtDdNBxXU2kkJ6RMLhYi9LO8oKjIJ3x50GwKNY2G\nRVU2S+WZEpn0QpLt9MZJlORceqYOCE1nPuzlzd9lQk8+w+l6aJbGCUMZ7bBDymtJ14SEFx+fUfv9\nt9+Dt5w9gJ9Uv4Npvkb3KxKUjdxIcB6VtTt6wzDPWs6MbO7zvmSLxkQex27BW/ILUhiijda899+H\nWWvw5Pw8RKjveeg91F9SMlxa6+sv+j5n06wK1YgBE447mKE0b6/+MT6lvg3Xf9U/cp+3O8cmAEzT\n4Iy3yfGFOpKArKfiWdRKIaPE7YAbrBFyjg7ejU3lRAJpue2fDf8vW2bIROskGfpn43v7kPPnFuFS\nZ8+0D4+vdaFGMpFyG7uoCBFdNjv/TBR8lkwvidxFkjh6axodapzbWrnpkRgz2+t+0/mJCdEuJ6T5\n+u6T8uJIwVYlatX3z499Q9IP/mT9TFjQzrfth/N/CoAT4vuT9LOLajxxY6tDmwdrkc06/9hl6aOZ\nLP0XP/MZvBs/iM+ecdsNy+SNVPtISoKPKSmQZrI5bvy/V8JXFlf5YwLE+Qfkf0w4Zw2Lgnuj87lp\noE97Aflvbm2jhgvvYxMGapUMvfPnxamp9pHFVYGeOcNVrIgC4qLrK63kzwFdlNDoYcD7EtBicc8X\njuHm+NsBAKtbOzujNjYQEV9rCxjFyJ+LhlgR04T+TKv1TR0UHNZiRFXXvjDNRxLNMv3T682iMYDz\nMOT8SdlTyA1U6FJlPkdWTZeiUjzJC78XgUf+RDWO+u4aDWJYbbwGXtJ2uq4xjF1rCKabJIElx2Ei\nEu3b1F+JEbN0rlOZGFfAlLZFZDUSP2ulwjgZUm2Hl3qqHirRAE5y7cl0GJA/54Tono+sfI37HmFO\nBc7f/WxbVEtrFfl7ZMre0z4C+de085ekrxLqgTRRzvlz1CEbGzYAg2ipnYqd6ULk5E78hVEzcs64\nvoabNdIhk0HwJ1sbQTBwvm0/nP9uZMnejb7bDqTU65RStymlblsXq+ZXYjwpYlHkNSpTlIobn4Vi\nL8fVBacKALccP44Pq+/Bn8cuRWGl8xf94nW80/lL2me36uJa8Pj+euXnGhvMyERWE1m857JniHMH\nvrTHjpCiEt7dCwCmSeoKUqARGXetxhhMt84E50/3kVW7F3lNxQbqZ0acFKTBLxrPFbJldaxQToeo\n0fO0AR9d9u6558iXdpxP5kMaG6go+B20vPMn9CxbcGhtPL8a27DIJ9MxxpG7Z98Nla6575ZIf4xh\nKSq5TSg8CnkOWjDlwi3aBvd4wZMCAJG/GG6v+3P3OGdDKPjE4Bo6TgxT1qgjl6eKDTxtV+YZRopU\nKlxfIKZhI7IU6qnx2DlQg4ica6B9EtmELFLYpuZ8fb94E8XTCwveg8eO0+/Cs8trAVLE+yumI3+F\nPuGrLWrZclxE0wq2QavMtrngP4tN+BkA5FFA/hrKo3+mfdI0Qa2NFzwwzy/325BqH7n9Ykk1BK7P\nkyW1D/mbpNleoyDn3+PGjnwfQo00yS5cj//9cP4nAdquxtlTAZze47OtZq19h7X2hdbaF1511VXn\ndFEe+QskczoJyTh+mVox7dMszrg7c/3BN9UTAMwgNrV773rJO4bin2B6Bvk3K3wFly3/JmoiH0f7\nEIUxw6kzaor84HJnn1AiC3DdSU3EHUIVrIpQVjUmW6c958/taytB2zSqVBEm3eomNy9DcB58LjG6\ntIowXluDVj2f0GS+vhcf9Z9b3x7Sc9sj4at6Xi2kldqJHJn+EZRKnmXeocUiz7Fx/CGMFC14PkEZ\nFDeNPId4K8M6FN7xew7XJ3ecCgIAprqkOqwUKPj45pdhyOmHhUzDWIs0omgVMfLJFHUUoY8aSjjC\nzbUNjJRD/rlv6x1Mi+cpk+FZQq1GlIsspVolk/1vIoUxIe0Bta3gxSpZCvPhzOmdnUxLQWNWKvTb\nz4vCPw25eA8FxeoTvlLqTD+bikevVRSqhXlx3sv5i95WAJBnCZIixRSH/LGAmfyMBD+iW2rZYyAH\nmp9hzidl6e9VK4WCagL4XplmToQUO/3KcPNXZPvh/G8F8Gyl1DOVUgMAPwDgA/tw3HMyP9lFReep\nsXD+or1DbBn502Q1FuWAQ2vaXo4G+pLNfdIYCPzrks2D4kApz2E2kT9vI0ifizg6acpMuTjI/X2I\nJmY5zwOiT4xRQKk5YUjntoApS0yisPF3qSsY0EQ3nKQsMd5a9cifk6q8AXjflg3qIhfXt0a8qyXa\nRy5OhXAeJgI2NrboeFQDwfe8FBJj05oLYOTCKL5G5BFbHUU7nQcXQgmkm00nMHTNPWM8sls79iBG\neBydg+WUznqNdCkweWII9bcr7h0j37P7nYzatND5+0hQggiBrKfJZuhzw1JdY5DpQENpxEhHQ+KX\ntUPBNLaPP3QCQ+XuJdCK7vyzbcAroWYp8kDbKU/7OEt7TXqT1T9+8ebIcllIKQkVS5pE5jmkzr0o\nCzFPuTGextYujet8hbsNOYmU/j9gExgVoSaeJvbO3x0ji5b8FqhaRX4zI76OvMixPdz0O//xWJAV\n7hL5TwToqvt70z5pVeMAEn8f3KspqJEI+QvnfyH39jpn529dv9Q3APgYgC8BeK+19ohS6ueVUq8E\nAKXUi5RSJwF8P4C3K6WOnOt5u4ydZiSKQs6ccM29YlsL2icgf34Z2XaCgng45qcZVfRReb01EDjo\nZZsLWVqgAyBQFuu5fWdROl8fVbPF7C40B4e90rnmURzoBKVgdLPDpYkAm6ZIVKB9KmNhI3ccToxl\naYLp9oagfVh3rsU9C+QvnMfG1tDfs1+cvPOXnHHkdzMKyJ948n5wmLyNYmNP2R3IPxTJ2JkiIU4i\nF8JxTbaGnpyMiPaxxmD79AkM4agSfjehgKpoLHgHrwnB7AZx2LsVRjU6te6i/jKy6E84//FkJPIN\ndEyjsUUyxINIYVSM4ea2R5mRDc9p+/RxbKPp/DmK6c9EMVqoS4oqtKeYHV+p4MqNUsgrRq5ES9Hv\nJG2RUjO/hrxVFukhVLiWlfZLDbdx0EYjE91CeRHhCt9ICB4yiu4OYQytIq/0imeca66WcQhT+pnr\nKQQI1VJZ4/TZTf++GRykuWztLFRKIpLxtT2M/MWCnENjGbnrLxYpTLgOhxcnGl7TnkhIz+Sqzqft\ni87fWvsRa+1zrLXXWmt/iX72ZmvtB+jrW621T7XWHrTWXmmtfd5+nLf1muAQj0zkrp10E/gwRn6P\nW60ixJb1887OntrEytUOjcZ+YxNC1TMTySN/FCGRiN133eJkV6V6pCRQdMymamOvJLJPyNHflb0e\nDoAmWxQasQVOETBZhlwtY8VSt0TrimQUDCKCq9kkQZpOkKC5+XvlW0Q39eTZIEyEdZqogZYKkYlU\ns5hIYUrJxT4nvOh3k2Wp4Gm2iJh9hpXqBalcFHhej6boLRZCrufQsvvaJbkjVHWF0XALKSX5NJr5\nmCUESsJaixxBMbWRhCRpKGxzv6t3ofIazh/BJH04zRNBYbFyyeLsusuHMIKcTLYI+bukPY+bydYZ\nrONquoYmuOjN1rqIPBX3srderRLmQRH3sWx5fFmUZoa2oM/JIsKS+jDJ8awRBAhy8a5ETYF32AZI\nt0JyPcwpgfy53oF+d8C6PJbmjX1mou5MLeOQdc9PR2EnO34nRVXgFG2wPrCF8w1aY5oJtZtygAEA\nCq4ZsWnj+rwgg8e/suijQgQNoxQqapq1A/kLNZ6eqU85n7Yvzv+RaDxBIpGA2abk1mWYkGzOQqvY\n0T7CGZ85eSYkf2gicTQfzzQGqzztU3in2UgESvkodyBED3meeYfUQ91INrPzV9Y0ildCbx9nOgoF\nUzpSoeDJBIfEzv8ATeIaOvRJoXsq0gyjOqhS/CJlGDk220AUg+DCxjrw30z7eJ3/QCJ/hSmFywNP\nG7jfJUvBUXPTssb+uOLZVOhjSbRKDrQPTSh6OIXQ0E/Gw+BkyHkUWYYtekfLNgsLHrcFsaXoax/a\nCADA+jbLGVVwNFzB2Vi4A/3S8x1Pxb0Izn+YJJ4SCvdSY7TpotVlONQ4nSaA4oKnkPDdrgtUvH/z\nTP+q/gy4yHuBDvLUFNE+CtYnh3UMvyuWUQo1RZY8vlitMo5DTqnyz0O8P/q/TEpU6GOZnb8Jv/NS\nT1hMh0wPBtDhnaugfTjCWSJwouumc4Vw/ge984+QUATDkstaa2zQzm+XWecbdJkjSWeQPx2fd5Nb\nsZmoZ+D5GYALswoxHODipn7casv39ukdwBWW20Tggtkl6/wbCVJWRNQOpboSf3b+UdD5c/Js9aRP\n/jA685JC6JlkJA1AUwqkp3zRSlPq6Y5Vo4d0MvYT0jl/eUxyQCiC1E0gH7/FYdTsYBiqXWkiRQrF\ndIwcyzhgqBgFLtx0Iao7X5EUmJDzO2AST0sxU+uQf7i+5auDOiehHwfaJyy2ab+P2NaOZmuoHWZa\nBw9EDiUSk8knxsIzrFTfJxyNErkdE5wH0Cxsm07HfpLGtNtZkWeYUGRyhRkG5x+7futORknjptxs\nOP/NMSP/nbSPVBnVAvnPFsABjvbhKtMizzzm9u/PWiTUNZL56SxPvCOUFMMW3cuSzUWbY/e7Wdpu\n6YkuAl5B5psMSikxc2RVD76HjYkUjJ4ZX3S8jf7jwz2zAki4Fv7Z6MwGKgy889fWBhWW33VL4yw1\nBJSgw/qEb7jnqudUVLE10IigKVGsLLVyZxCilrFigkiAd0LzqjNdY0QdVA/ZKTRiFGmChD7nOsEq\nWHL+5TKDhpnrg6F3QotTHHvfYpRCVbkFyCekaayn0TIOg3sOXTiXfOk6f9JgS2fJKoe+qVEjRl1q\nQfuIRM3khFe+FF4C6I4bo4n86yiCsgYDWzYSvrOtDoCA/Cv0kSRb/nw7qCRaUJZtIdCjQGaMfOIo\nOP8oBOwS+W9ub0OrHg7Q4K+VDZppVl2UKaaElA8T8gECJSCRY1FrFIQwY1v5Slrri9BE47neAAeQ\nIkYNrSJfKBfyIe6/ST84VtbnGxV5Pbnfda3SqCGcP5RfXD0VQT84tXS1P2aWp97p8j1PkgkKUmoc\ntClq9FDXNaooRh9lI4Ipsi2fDASA7STw2nxevpfCtyIOlIxRkRcONJy/6mOFEH1la4/8g3IJmKbc\nioM6feZ5UFYJ5z+kpOET7ZoXFjCIkJQkAGgKOFaQhSaDCEWEfI0mioKsU7miOkCoyei9rMdX+kWM\ncx7unpuS0LUHv4gCAyxpTr6GRdPfM4B12kdgIBYtTqjKe65i964iY2BU7Nt5cyW8Ua7wS6MXosVI\nYWObeluZkM/j2odDJkWNGGWaIKfeVn2UjgrieXWAOsSaQsz5kJNj8GNUjMjFES4hzeN/JiFdRT0s\ns4KtY9Ok/bRL1/mrEIb5akPKzPe1c+CmqKHBq7NolVyuI9mB/FmD7RAhJyvr2Ck5YpjGQPVOQVgN\n7lcSI58MBSc7g/yJk3XOf5ZTFIMrVgGZKRU6XIreJido79WDJrSRDcjRnS/PUiSU3LtMT4Pzp0uS\n4fd4kiO3zlkfwtRfK9chSMls1lvCis0Qw9EL3HeHcxJcubvdC1sX1lGInmarpEenN1EJ5293kXry\nexr3DnmFR5GnhBy1p1SSaYqS6I8VU7hipDT1/eCVDZRKNhkiw4qPRCYpN0OLMKvqKpeYh84aAoBA\n+4T3XKLvJ32NKDh/dg7W+G0NmSpzjeGkI3QOju/lkEmCsIAjSBsiN2sNSuve9QpSGFoIWLkkc2RG\nRaEgL4bvFdWzAVxUVYWt6Eo8yZyh+wg0kpe30js5u3ofrIqxRC0WNCTtE2i7KauKUPpEKy94sVhU\n6zhGHzViajhXzzh/KABV5WpLTHj+61RI6CNQE3o6LZscVsVIhiO/H3QftbsOor04ujtosgYtxZGJ\nn5/U6ZOpKm7qF83o/GvVC9HQoy3h+0g0TmBFIqmkCeUMjIYhzbRD/sz5099GY8/5++QZc8aU0GGK\npY4V+qga9JJBJJJONDisDeE4esiTCWmXNaHEXaikmTyCQ/5GDC4Vqi0jFdQiApltThzKWaHmUbVq\nhqiAazOc9lzS7jKTQKsejDENtYgvXNlaR6GWEFmnZNCieZkCIIvl8mgJKyZ3zl9FvtEYXx+j5TO9\nqxucrHtuwfnzYnLyvi87568DiubrCglfeoaie2JeVZ7W4DxHlmSoqEBnmXodTYab0D0X3Smj/DsZ\nDzeQ4QAO2hTKGmRV5VoJQPnFxNc2UJ6jyQfHHvkzWrbWolIB8bmOSk3OX8P6rRTZeZW68pp3pn1q\nbXyn2GUTHGYduV23ZBctvfwAACAASURBVPRbVRNPPy4jB3qBpvEJe3ZKkXD+Kuj6ZcJya7SNJDqI\ny60bZ1oF599Hc8HbSF3rjqWS8wI735+1FjUtdH1UgvaMdqhpXL1DiYiEGwU9KxkhV0UBo2Iseecf\nYTihSmUGIdZ4iTBX306mE2RZ7q/DQAHcMZYixhWTN+cnuMgL/lxuQXWcfzlb5BVxYriHJRqDbVvJ\n7rddss7fgHW3AvmTqKSnXdIvGW4R8jeNLD2iwtM+XpbpJ6aLGuqanH+k0Ld1o+EUo2AghHZ5Vfvk\nsUaEPB2D+4HMFpgxml6SVJIYXN6pREpw/pL2CZMzIbnaQAx+WS0JOL115pG/+3xeV6Ezqq38M5yM\nVpFjGUumdHQOI0fsrEAuVR8D5mSV2qFjZ9R6ov9UfHVNnSh9UVu0Ay2vnzqKUjh/o9ySK+/ZJ8MR\nnH9dk8MU95zlmUdwy6RQGY+HsJGlArjgmCbrp5BhBcsmRw8VitoA5PzVzHsu4h56tqJ2y2Ihm6EB\nzzx0ytE+POlV5K8+UFjW9woK9SZa5H+ccqk22tM3Ax0cZhVFpDYJDjMdrfk6lYEtG7vPRZ5T54Rl\n7BcdrRSM76MUaIvTp1aR4gAu11N6fxL5s8KJnjnJLfvs/EXOxiN/hH5NfVvDqgjWWCFvFZw63x8t\nCBm1O1Eg2gcKKTej4/uIFKZTFw33NcuD7Q7nnyUZipr3x3DybkPfF70elDVE+wg1HucYfWsLpwaL\niYLiRoYssTZKoa5rh/x1mMcXyi5Z5+8VLULtw8i/X2toRBiPt4PaR3DpOjZeAlh52scdl50/V+vV\nseNzpQTNSERIx9yeOKfasw6Z1XkCEym/8DSRv8sj9GXLZSXVPjw5I6+ZNxHCrkjMTUYWGbWV7dGE\n0koJzp/OV9chz6CZW048LdO3waEkk3UUWMaSrtGD9j3rQ++VsJDNJtP1bHJPOQ47Uyt4XD32f+Of\n4Ux/+dHoIVgVo1+GhBmjp4bzoIZc3vkbHaIdSjcUeeZ766wQ3zuejmBjdyypEkvGZ5DhAJZ1hT5q\nVyFK1KFX5nBOJHZqFlYVGWMakSA7u4fuPYkKA6ywNDKK/RiLxELGhXbslGqjPWhQ1jnZqtQBMJiq\nIVvtoWoAhunoLCoMEBunQvHiAYjxpYTzZ2VWpHziNhZS4tVTG7AqwsGaW0MH58+72XE0UPZJ7VUE\ncGLUDGBBoAN7NO5MpcXi5Ph9gGmfCpFxtE9JxWFSEp1QYWeIFiPUlHjt10EkwM+ecwNJNvGNEpnq\nNVWOqqxRRgHUGISEeViQA23mkL/j/LkOwbXOdmMymY4bCrYF7bMPJnuVeARGdzvQjvbJJiNSlTS5\nuvGyS54tm6CckIlFC+V3ZKqjCD1TN9AVKxNkZeX6lgt5D1jXE70oMlIFNVGmPyZqoqx20RHz5EQc\nFAtRBG6UJnubcIvcnhZoW4UoAgC0Lj1t0KfPZ2niHXHfVl4GWmSbyLGCQV0jRg3LO40hcioLiRwR\nI7aMfGT0RBM9Ulhb20QpnKDshBkWNsohWNqBTDgPTvDKaIclqn7TES9vDU85L3JP+6wQ6honCUxk\nwZWa/D6LdOSQv67QQ4VSOdrPqp1OvYz6WLIFuAGZzt3OYb7qmsbg2dU1N+mrEJH5mgXfedL6Zm/8\nXirbdDQGEaqi8hXNAx1USi55XSGmCAEAxtunUaGPvnHtIWROSYGKIukZ1WJ8uSir6aitUhhROw4G\nDVI62vfRDj0bKuYb1IL2obHMY9EitKLo2xoWEYq88ItTZETCN3J5BaZ9KtrJDjYID7aGrkfYgPn9\nSPmGeQPuSAvrr3vA4z8vUNCCO6CEb5klSJMEOZaxrEvqEyXVPjvBWWwd9ayVo+fcvQJcVLq2vgmj\nYk89zm4dej7tknX+uyL/KHZJP0JjWTIVyc+Ajh466JQiT67WBO3jrEdqnzJlfX2EvtHNRYYcYeRJ\nCeDsthuEB6xDSGWRUaioGwoZAKhi1wtGhpAyoSQTcj2hmfcLlEfWCmam8EtHKiwkTPtUocJ4iZxN\nkiY+edcXtQ1lPkGOZQyqyg1q2XiO6TOv2OEaCuPpJiAkvKwCTp5edSi9rqjyOihkvGKKrqOKCImR\nBtUtZDuPWdCGHbIHjVeLGM5zlChJmbNMiCwrEtgoIH9+J1U1dc6/rh0PHSlYX03djPDqKEbP1t4x\np6Oxa+xmmlFMOj6GWvWxVITF2/ejEo3NagpVmJ9mtZZvIqYiZFmKOnbV3jG1rzBGUx1I2XDyyegM\nSgzQM00lnCWU2qQtXK5CMW3HyXVeaCMgo4I3RtY6inxr5bCVqbuXioDCEsLf+zoNEe0Y4fw1IhQJ\nJezh5hRHoTX1iXJSz9i3Qo9o7lmlMKRtGz3KV8pv7MoLqkYozvPOv8qRkTpnybq8QZplmEzHyLCC\ngSl9xAG6Zs7DNJA/0T5aKd8ZOPQoUlhfc21DWAG1oH32wRrl6swR0oCMjBvseTH1EkXJ+R8/cDX6\ntsTXpMdc8lMkg5n2yYspdK1RqV5Y3VtQ+jYVrrDeuKg0DY4mj2mtRamUb9xlZ+/H2ibyl5wso2CP\nMpWvrox1oH18wpCOrY32TpydVJok0JHbEk/K63Tu6gb6dYWe1Y0WBjuK0CifwsifnYdMSK+v02by\nRqOHQD9ZSLUPvb8eVxwHtDVb5GUBjFkqyEU89B7kglfrEnXswECfJnleFmgWB9K9mRIZDmCpruka\nox01FWyaZJ0xIf90e2OG9nH3ksMpTpZz5vxjIfUMyJh7SsU+z2EaQAAA8tTlL5zs0S26VVm4hC+q\nRmSZjs+iwBIGde3aQ+ygfcL9aMToWeNqWxRgbHNxMgooCG0P6jAOWRYdgAktokRNrdDAM1C+EEtZ\n5Y/JhU6O9oyRpgzSDNGrvC+GEvvmRiiKoPZR5FyntM91X7uOsyaKvISZgY5FoA95EcvLwktbOemd\nZSkm422iPSnimE34ivvVyqn+mALkjeI5J2GVwvY2LU66bsiDL4Rdss5fJvikOqCHGorRX+EkcJEl\n/lRIFA9h6gdCYQIKjImKKfIcxXCEmkJoqSqy2KnJ36StGQ9RQrWqKhiOTgTPWhWliyZsk0qSOv/Z\nsFJZjUa1q+dPg/OXCgNHGxjRQ72GjiJX3ETOf5pMYSLngGXhiinHKLCMQV15B+fumSt8m7RU5JVU\nsgkb6G+AZBgGfw91ozBqNklakzJliTbnsCJhyFSXhsL2Fu9RzDrzJqcNUF+ZyD1/XhizvKBFjGkf\ndox1A/nXkQzhA90EOJWRzAElw6GjfUzT+Rc9BwJWSlYBhcgovD/rC6n6vHhHZmfyOp2iJpTPycQ0\nSVCpnlfD8DjKkiFyrGBJ103QwchVjNla9RBb7dUqs0VoVimUlC9ZogW0jiLfosO3pmZVC+XcDrDz\nVyFy81QgQt6HufZ8kvvrky25oVzkxVJPTREcI2soIKGcV2w4X6A8yu/73IWgfbiQqy59DyBuJ5Kk\nU6SJQ/4uUnX5B2tD7UxjfiJ2nD/RPqzGk3UIk4QT0s29Ci6EXbLOPyCFgOB0FJA/4F6wm+wkUWR0\nFC/jgE08Qk2L0GiVX3iZpxhvrqNCHz0T0LElSilsueiOeZY2wz5cc1GPiyAiUQEIAMU4g4mjcMwZ\nnX8jLJeceiSdv/vf9Th3V86cv1ZRI2EIANpqHxV5HXyaola00Y1BSGzVjvMc1DUiYwRNI9RIM4sT\n10Aw3y0dYcpSRm3QQ+XbSUtKyzujvru2y5YPuapLFVj8SMhHx9RDyCdJoyBvZcqiNlWgBomXKGu3\nIfpswtfAIMVBrBiNHirUceTb/Ur+272TnnD+MbJJ4mifmXqAnBayQ/5ZCUcoKRCuL/HJyebYBpxy\niVE+3994NEQVxWFrQY5+S35/YVF290hRqHBeNY0vHsc+MhHtCUpangZ1GF/lzKY0/nisj49DMeQO\n2g6CgjGO9smnk0aeyiCG1lRXY6mgDspvZiRVcRlvbarhE9x+EdPWX5+PfCksyLX2ff8575GWJfJ8\nROCn9s9a21Ah3QBKgkpj1RIgaB+lkCXc7M2QJHpB+5yz8SRuJCBV2GcTACpTguV6kuMtI9d2lpu6\njUfDwMfSJC7LHOPhWe/8FVyfIOimMoEH9xZxiYersFesicIk9snFSQYTu4ZyDX6fQ31KyPFuRLEY\nSNYXorEaBrARF1Yxcox8iOopEOLuY9ReupjmGbTaifytyZDiAFbqCj1o0XVURCZ0z7w4zSJ/3/pC\nARklPPtao2e1KPJyeyvzuwSC8z946KB/tkEhw+8dmNLG8wMTOGc3OUW0Y4zj92ERkfOvKFnK0Ri/\nkyRagVY9XG6N4/zjGHXV7L3vWzozWqZ7nk7GjvaZRf4Ddx2XU3Wzc0rNhcwo5flydlQmsg1HCABV\nljUoTQAYDTedEo1AhO9YaQqS6mpalJs5pSat2ENsjBhfdC10DquU79jZNwYR0YAsudyB/Mn5H4pD\nzyN+t6w8syok+HvGAaQqmYgx6/j9uqphxULtevsQrWIYWUcoiEuPNf0sEguOTDJTRTL33alNvYP2\nKYsKVT4RyJ+iSKMbz89TpEx70uLkpZ4Ic7bMmapSVAm8cP7nbJzgYz4QADk47Z2Priua7ACTIUBI\ndPXJYW5urYdJSBOzLAqko01UGNAEc5GDrquZfIM795Tbz9LEqIwbEIys+KVP1rdRRX0MdN249tlj\nekdqLLhr4Cz/rSXVYngRaR4LgCvoIlkmo86iyKGj2Bc8+etQORIcxEHtogTeVHy3CmTn/ENk4xvZ\nCUeYGZYyamoDERJo8QxnzHLGy6+4PDwz7/wD/TJNm9pu45F/KPKqTU3a8bAgOBkloTXhBDcHrgL5\nql7Pc/4VLVrBgYR77nFhDyJkSeIWspmqTq7IffzjHu/flZ1dyGA9DeYTqqqp9gGArMwISNgQuSUT\nUqLR+PLjqEKBZSwbuyvyZ7BkiUrxUYwKvZ54jGiloBXnYRRVckcoMpY1N1tasPNfEYV8IXKDf46+\nIR0VYxZp1shzOHlr1UgCG8SoydHzzyyAXNf++DxmmErr0RdauQXKAR2iiI3x2/cw8i/qAlUxagge\nAKCqyqbUuYH8QyfSQPs4oYeFQlkxVQWwJPRC2SXr/IMuHoHzV7GnMQCgREiesWYaEIkamnBbmxs+\nMRWQf4ZkskWyOY0YxDtW1a60T96j4h9yGrUmHh9Nqedw7UGXkNP1TO1AUBBZIWcMUsrQ56bnUZTy\ne8v2aAa6ULvpCDUsRUXB+edF5bsSwtKTtBalstCqj8ujGrHR1B3V+MhEKpe0ogI6uo/A7/K1IGwC\nzs7DF80EqSD/jBOGj3/c4wMapefm7xkKKS2wA1HYE2gpumdrA/Knn1XaOb6QhHfnPbH0JADA8w4f\ndpx/HKMqhKxQqGZq9KiZnbvnKkthECOy8LkZACj67v9rrr6axmuEsNUkU1gB+XuprmqidDcW3aYo\nygZaK01T1FGMmJy834wkqpFjGSsK9F7CuPCbuVDS1kraTsn3R7ceBYqmT1GiVhGKzOnoZxVOvLva\noV5oOe0VYF41hYb4wDXhS8AV5BzF1JWrOlAC+XNLc5m7YN7eIX/diGB64pxBXs3v0fo+UywTraoK\nVbrtIqcqUGxFVQRA1YicAtjUKvI714HmsduDgFVjqpFDuxB2yTr/BuevXAVUkK7RS6fJKAc94CSh\nsTXoUag9noyE2oedf408HRPtY6AMh56V4OdDZ0Hdc2oM/kFDgSKQ2XTrFHGyFSKEiSMlqRbKq0C4\niKSBHPkZKAgqiNGICpOGkT/RPixRBICCksAODTknq3WFlCbulQO3Z0GtnPO3Ajk2kL8JixM7mh4C\nCg5bF4IqgWWhXLO3P1NMVx4+DFZn2ZkiL6uAnKSeXsqnwvOTO0Yx8ucFr4YooJJRW881dXv6k57m\nEJtC6NPiF3lAG9ev3skoHQ2YlznJKEOoDwAlJT+vecITfHsPfm5hUQ4Ln09OiijG05dVJX5GtF02\nhVHKJToF7eOc/woO9mPngLxUUaq1wj63sTF+QQ95Lx5fyitzBhRVaxVhmo7pczPRDm1ec4CqyW2k\nfMdWXoCNEglfcrpFUQiqy30uS1J/zZ72EUl4Hh+8i1h4TypQuEylqShEvtL5gyMQkuPWNdJyjEKt\n4EBZ+uef5ikaLZ0F7cMJX4uo0biPE9KG4ymLRpeAC2H7cial1MuVUvcqpe5XSv3sLr9fUkr9Gf3+\ns0qpZ+zHedtslhc1RnvOnx1AZaXTCvpil6DTHm1NSGoGBNqnqktUReqcvw5JTV2RYsTOJM8iJ9+M\nNE8265GBRAtpsukSSiz98nSLUGNAeT4yJHyDZrrvnUfQjg+4eEoif4+WLUVFOujg69pp7VH7yCTN\npkhi1wPo6gMDj255YxpGYU3aJ1BvfgEVaNPvuzqD/Jv9kZoJw8MrKx7ZzSqIjIq88/dtIITCiZVe\nmhZmifxrHg/iPrTWSOIVLNkc11zzVZ439n1khMOstEEtEr4abn9kgOm5ICrg/jDXXPEEEcXwvfBX\n8M6g76k81XB6PBY54RhadpTQEIsOLyyRRoElHF5ebryroNai8cUbnrBUUdB2sj0B93YaRIH2yTLe\ntIefv/s8V8sfWun7v/fzyo8J975iKyL0Kqh9eD5nKTfro93ZVAxt2dErn8PjyFIRst41glEsG639\nz2ookXimRaiusU3P5XCRioR70pifkvaRRV5+1zLA59E4GnhUcv5KqRjA2wC8AsBzAbxaKfXcmY+9\nFsC2tfarAbwVwC+f63m7zIfvCOoOXt358WplZxKpgq6w2vO0abFzr1Fdl6jLDDUjf1Yh5Bkdk5uc\nBb66hyogC9UMtX3Ct3I6+oFu6uu9U8Is8g+T2zsPP/hCiNvnBnVR5FEKv3ytQlFV0MFrag9QE+ev\nkKUTbPbdVoFfc8VlQedMyF+2B9C19s4/ItphlvZxvV0oLKfzB86fnXCYEJwMPtiLd6I4gRxLHZLI\nABW2UZSlFEc7QQEUGqlxYp3fZ4S60iiiAZZQ4HFXHHbvJAqFZJJiKCrtaB/DSb4YtZbIMyzy7Pyv\nOnDIT/rA+Yf8BSc/+3zdlLCMhCOsGflbG2i7qgJ3HW3UaURApQa48ooryCkJ5E/o0yqFnNQ7kQlR\nkF9ohaPmZG4/6tH7i5BNgoLFfc59xkXJNVaWDwR5sn9/YRHSivYopnspq6JBxwFAMpnQgmV8tMOb\nzUAif/A8cfORF0/+mTsn4BtB0juolfXOvydaawypL9IVZSaktiEh3VC7MfLn52fCtXBCmmnZiPIA\njzba5zoA91trj1prSwDvAfCqmc+8CsA76ev3AfgOpc7vEmf9JHbfF3VFGmxueAsYQqQh0TUjoaTR\nnlelUCUQ7VNVqOoCJTl/Rh91kcGqOCB/QVnIqENbN/Bj8OSkz5nUOX/DuYBAgwQJWxSKf2jw7zqR\nxM8GcdizOFSIkhMm5N+D9k60hCW1jwaI/80mY2xR++VnP/6qUJRizA7kmBZTUiOxVDAg/x6/ehUU\nSrGKm7SPKL4LFb6kE+/HgYrYgeIUSsstEYg2iqw/Hie+NYIqi8eDBldlhkW2JMlrz1Y4OIihjHPK\n3D5YqrqySSKQPyUhGXnO0IC809jBpZiiiUi8P8F/c8LXP5cwFnjyVnVJFFagvyrtwM6s8y/pvE+4\n/ArIPYClCMBCIalCwRQj/0AruuI4R/sw8o/9IpYQ8md5KydwCzVA31YYLB8Qize9P/rfQggzvJpG\nFLbRMfMyF3OCngM4ioRfkH1OgWhgC+VFAgEwKMqZWJ87MsoVhbr8DV2HNhjFTp11pclEfkVusBPy\ndxy9+oQvXWjozutkxACgjIJsC38hbD+c/1MAnBDfn6Sf7foZ2vB9BODK2QMppV6nlLpNKXXb+vr6\nOV3UjorOMqMEpPbhZBP5NxtaxdZ45F+IhJ7fMcoYUozEJHOjgcBVhjzZPe3jFh7euE/D0TKz/LJW\nBQq1giXiiQ0iQKh+2Cn5hK8vXomC8kVhJ7KiIi5LoTYrEwBH+7Cj8Pw3Vf3GqL3DzNME0/gAlDV4\n8pVPQgyubbCBiqBJPaayeon8vYqDrrPR2CvquYQXmrSPVED45nNRLKIdpg3CIsl89Q7axxqP9jRE\nIaBHapTwtUGyV6S5yxVBQykFrorlJmLuXTunkk63fSTI92wsVwLzguJosmF8GIf1BL0o2hG5+cZu\n5PwjqzGIA1UCdnr8riz1LhIJ38q46ljvCOGKkfLIFcg9/uBS4KK19lECO80JbSLjUaqgEBW1LTAq\nUDr9eOBpuwmpffr++VPCHq4h2tKBwzuoLlbZOMBCETors3QdqEr6i6JIvcMN0u2QUHVJ+AjahlWF\nwYWh+RH7cwLcNZTHkYZCHVGbFRr/1mgkkUP+j4ubdRYsiOC57KXYCBW+/l7puh3yD7SnjMT+f/be\nLVa3JTsP+qpqXv9/rbUvp0+f0xd3+9oOdpw05iRuEgUBtoWfaEsQyEtoIiwrD4gAIsIiBksIhBFE\ninijcUANQZEcBNjCIcFuv/AAErYUMCZAGwyOcbvd7tN9ztl7r9s/Z/FQ4/JVzbn26e6991F7q0s6\nZ639/3PNWVWzatQY3/jGGO9Fex7Cf++oyl/HNcg5fzrn/EbO+Y1XX331mTrFQUdAYURY9KVdI3AK\nUL001d46xRyza2wuHE+4ldXZr7BF+Vg45m1+GNX8uwqSIchJTWNJXHPoe8cPBZtVoZQRcCK2j1Mp\nxTqJurhIywlFYNbpHfSwIwc51B9SNnZcXbO6vr7E43jAEY8x3n+lVFBCBHKt+WcEPH7nsfevWfyd\nBowFCmJK3Qb2MeqcjOFWhP8ssE9FHyUoQuvIOkPG/Ryc/VM5/aoBLiHIevDgwNsnT6A1H8p7LULl\n+lTDPjkAjx+9vYF9NI+Ms78KNfBL8RU8XEoaioRF4Bx5f0b1hFiHC4ah+FpKMF99eK/LAmXDqJZ6\nOkkQoWn+xX/xFbHcPngYDbbLpxM02FH9AI8lLYKuT47TUOEPEKzYDwb7vCNpxC1fDUpcymWYMa03\nmM7O7f0pi66LbtnkUAKyzPGdT7a+dG6uL0t1spCzxUWo5s95tdSyLHvcocKIjEg1lk0hkvEsUeoh\niM+r9GM16PHe2HttiKurStnM8BQXHOeiiU+iHk6AwT5/IDF/FE3/W+jfHwbwO3ddE0LoANwD8OZz\nePadTeEc0wqurwzLN+0viMaa3Vxbb0oO/bSu6NWcDHlD9VzXBTdKo0SmaGAVCnXU8EnS43b2b6WC\n1TUHrofy/cXxzDT/dTm5iStCnXODG+wjYzcTlxg2fSol5VTzj3C4IwcXthbAg4xTjLZ4gaJtlXHc\nIswzLMmWHQKA5iN6+7Fqjo55KjOn08yPwdkefRoatk+EpovQudGC52Mq7wyiBQNADEksG3ghdI1E\npWR2AepDKf0MyHQgw9eDWAG3Ty7NGV7Gk4tWeOvpeRXee/LOm7gl2GcxEVRDEddXV3gzvIJXbt+S\n7/RwrP0XOYbyDrBgHgvjyPwX2Q9lS1md10oLXkj4Z0Tc3Cx4s7sHAPjQNNihvCpDjcb9WOoUW8AU\n/F0lWSsMBY39KFTFhCePi/U7LZ6Vdb1dJC32Ncbjmd3TGGCBNf/aF3OS/ldO7purCmop60PX/2pW\nlh1YGU6JFny/fWZERk+fnSRrqGr+y7rgRg6MB+dHO3yvJENvkHecEb3kJcFupvkHuOav6yMHIwm8\nV+15POl/AvBdIYRvCyEMAP4MgJ9vrvl5AJ+S3/9JAL+ctQ7iC2qG+esLurl2OldwnJOxxIyA6yeX\nhvkrPfIWHElKDlFd+CKYAeDy5CwQ074hgWM4GcRgqZUbZ7MK/1cevGqL5iRsh5hdM1uJ08wsEgCI\nCiWQcI1BtWWP8FW3yyqQF2Oqt8glcGiFba6bmxtJ+bAgpGRC5XRbKh0Z1TMEPH4igT6ra/66EbsQ\nXfORbg/DaNkZdX5csJZrtOD5ECM0+tkw46h+gGg4KrM5LKBLteVQ/BgRK5Kly9CUFAT73FxZsrYy\n38AaEm5OHpxjfo4n7yCL4qCRqKtk5fS6DRHvfOUx3gkXuDhJQW8TSqj7LWsk4YTDfO7rphGEq/pc\n6G9PKJZHxeC5vsGX030AwAfHHgFlDk43N3bolfmOuBTt3dg0pqaUuTbMXhSgYZyhKTcuryXwa/Ug\nvdOlRIav15im0f9eLbeKjSZpN8wRL5g/3MK+XbzPfki45q+xFwalyYHCxYxS5HiDsid0LZxCxCmU\nYjEq/Fdkgx7vXzxwh/S1ZgpwJdJKqgpbakHylN2r7xMtpsNspPeqPfOTBMP/5wH8bQB/F8DP5px/\nPYTwb4YQ/nG57K8CeCWE8BsA/mUAGzro8256klud2utL04SUrbCEkqdHM1yuiHj86LFFpvaKVUbC\nlpVvva64VWeX4PMA8PiyzixocE6oMX+FaRJpxoA7Aj/w6qsmgG4fv9NopNHy9IecLTjEYB+BLjKc\nJplSpGAw1RJLX3JkHrzi36FovKT5315f2yEGQDDKDnmhYDnpn9aeVcw/B8rtE1VzjLYC+16E/066\niNXmsLdQexeYOr6OoCD1h4hAiUSPVHhIDpWyHjwCvFxB2vKTS7MYdcwrAk4njiYtUNATgUq6ZTWB\nqUFafh3w1pe/hGuMBouo0LR3pWsE4nTEivkgwj8qI8nX9iKCLpDPZhFrzPPNlLz/78QDUj7hXpfs\noH+sDDVkgxgvLwW+pIRoqgCFkOzwNcy/P9g6vJH8OCPlk3r09pu4xIx5uUbXO2ynvqwuOhToEF3t\niwk5G9Ryc6uR9HDfh/YvQ/azWxam+avShRVd6uiZ5d32llsKFOci87xm3Irz/96D99uev769cYVK\n5s8ii2lP+PyBFDZZq+G9x/y7d7/k3VvO+W8C+JvNZ/8G/X4F4E8/j2d91X1CsE0MADfXjsuZpkcB\nQqqJXD5+hBM6CoBYVgAAIABJREFUxJwximZwu8PEWPJivPMxdvacq+tL4MzhAM8rVPwNynQpME1E\nyCfDBIFSIg4AXj87N83/8eO3SBiWsd2ohWGwj1Mpi3CtA6v6rgjHRbTlALgFRJi/49/E04fiyLc4\ndS4IjQUh2TCVJXMKAZfX18CkZm/RfExQxwTFyVc5gfp+Qrq5EQ1JBFeGOSWBUhZSQ+1DI5D6bjDb\nQul96rNRx2LMjukaxIOMnrROd/iW79lXpGtlRTTYzbndGZdXl8A993MsiHYQxayQQMCXv/QmlnDP\nNGOHI1DNa47BnO7H8wvgrRbCkutkvhJZlqfs0JkK9JurK9yGvmiz4rwGgMvrK1tfumavr67k/Xl6\nAlOAUoTWatZ3Oo4j0lWpOX0j8mvIrll/5Yu/XWCf05sCQdZjHjoXRaqZOxVT6zEQdftEfgD5TA/a\nCBeurvn7PtFAvtRJsBlp/p0oX0uMVgwnqsMXGbexZEq9ePg6wm/8HQAlJsZ4/jLvtydXkLQAjRfr\niUYJVRKE+YTIgn/R7aWN8F3huX0ASDWgwmVOIgFU+AfAXtrjR4+xhoRuXXGQouan5IvcNCv5HACm\nNEATol1da0YQdeooxt8VzZ8OHrVOKs1foh/vD7MwSxIu3/7yRrO4vtbCFU5hcy0/GA6t/e5ijflX\nsI8eCDnbgbDCDyzDVFUQwq0OALi+OZHZKzlVpH+FjVRjnmln8/fdYJr/7VJqt3rkdbnmJvQmMB1H\n1cOtNyvBngPV/F2btBgDuBDtzPzn+AJxrF9fmSVozw2R+Psy5hBwrfV2l3KIrkgexwD3w3zp7VL9\nSguHtGwt7bdabgkLzo4X0kd2XkPW4mpj4eLvS+icwYOI09U1bkNndQ7UUXotmr877Mtn2gmlMTst\nMzmkKYtj6Gfz2dweyh7olwIx5QB85c0vFthnuUaXoo3Z1icJYkt4KO/xFODOXeL0+2cq/FWQBney\nmjXgCpEeLoPstZWsjb73tXArZTCNHZgzbiV19uHiVfOPnTSxG5yNpzl7PJ9/ssACu46cu0lQgD9o\nPP9vyJaDYuTl39fiIGIHnybNUu0mI+Cx0NRizjg/K3V8T1JlKWRnIKw5m+f/bJ5t010T/zvQC75V\nzd+yVhbNP2UNTy/XPZZc9Q/7zoTr47e+IsJVMeeIK8mfAvn7JbggjEEgEDoQur43TFHZPslYN07V\nNNgnBBN6JvyX2wYCEWvn1vFX1W6vJLJVYZ9i9urh1MMS68oLGrvJLATNzaNWRwX7rA775ABzxA/D\nuNUm4Rq9WTZQyyubY7HvehuzxgOUdxdxe3slee3VMVcOiMVgN3XsR9ycfMxByjwqNOiMsoB3xB9i\nwt98InKQUZyG+qnODyT8ZS0Yay3D36ni36oF2/oqCdduQufWk1x7eVmnSsgh4nTSA8JjLRTiUf8K\nQ3njeDBs+2Ys973o3y/jAN5+88u4DjPm5abySemYp5GjftU/o/OQTbi6k/vk1oDCPqTMqRD2PVHD\nPhEZ3ah1IZxBNXWu+WuBeI+HKelMetwiHQ4OB50Wt8ZEaXhC9YQDhPYr70t9FzynUemz76FIfnmF\nv2q3UKF8WzTtnJGiVgKS4RPmfykpVuOacXFRMi6eUmHSsDay5NWyFJ7PZ37I3HJBCQ7y6kum0Ej4\ncoikLZfP3+mOAIBXB4eSHj162zVS0fKeCA87kObvmlk0HNoEYSwCdyG2T4wt7JMrn4SnZ5AxnxYL\nBgOc+XR9fY06WC6YQ7T8vcAGGg3adcUOCFRBaZqQpCzetTgbLUAMAet6wg1Gq+urwllhn2F0J6JC\nLT1DbBY0plq1QDzIGJJGP8sVzJq5KUXE7cATFs0iWrMKGo4s7taMpFBEcuGvlN7LK018pkygJoiK\ncGflvJ9N5z4Ws2ohY8n0/lzZAFz455BKOpLQo4dbLQBwdfUYGkGu78+Ev6RKqGC71LlwlT6Po2P+\nqwRyfPQjH5L1FfCW7Kt5uTbhzw7fYZx8LRo8q3snm2XpEeinykoDauFv6RPsEGRroOyZUZ8JlxfD\nUA6EJQQsEuEOmufb2JWiOePoa0SVN4VlQ8TjS01rXfwwRfkRCrI8v7KGDfP/pvB/5sYwCaD5T4qw\n7TuNdnXNXyGaa3lpIQMPX/sw+nzjmj+cZ5yzV/+5f37fYB8tZOEsEGEPoEO3LuZk0khNhhgA4O3E\nDjnR/B95uUmFp66uVPiT5q+Yf6fOT4eruqGHFp83jUnr76pAyRTkEoMEGPkBerue5ECoYZ+rJ8Wq\nQhaqZ/CUx8XslSAj1dLlIFqJLTIOE7pccuNoXVhlRawhYF2vcYOhhkqsZ8B0OJilpZbCaIFRzvDQ\n895M/Zwx2oaP5rswhtPpRiA7p2yWyF1PIqbWzslKO2Z3Qiq9Nbi2d3ur/ho9GFZ5f3I4Jn8vSygF\nfw6HElnKmL/h3yJIQs6IQUkKLvztPV1elupejeb/5PJKiA8wzXVRzHpVvwtBiInfn2ju09HiNDSo\n60Pf8ZrMdcBbohQdluvib5C5UPLBOB9lzMzGgf29a/6lz8pwYtZTjZ/niuqM6Jq/WXxToc/mqEhB\nxjjJgRCjOXyxijWQBb7FCWEYHHZba80fAN558tjmONr6L9crlFbiXNwyYfj3vWgvr/AP9cK4ubk1\n7UEpXuqwZaF6c+Nsnfe9/pqk8I1GP7Psg8hWlu7+w/sUWelCQguvAIWjXmAfhVqiaS58SDxOM87w\nCEEEEwA8vqRoS2VjUBGIKLCDY+q9bWJL7zAMovlHnwfj1Pt8KSy1mJ7sgjAvS+38tPTPl2SZiMNQ\nHKKaUnhF9CIdQ08+iXLvaTgabPBIhH8iOG69uSqprqkINrN9xmk2DVr3+5iaIJ7cJBBDrDTAlQ5B\ny5uznGrMf5UkYqr5q6MuBKx6KK5EDNA1FlzbvTWrSJ3Bau6r8CcKoqy7oSdYJKgWLC88s+Um2rKR\nGdzvdXO6KZp/9hgFAHgi9Q8cLomWDVNx9qo2RNe75i6fDfNk708ziD54cE+6F/BIYi6mkzqbFzvw\nIlbMBy1qUw64QJq/p7F20Xib/cCzZH2ydpOuD7hlmIRezIrAfCiwrh1CyDjIWlgiqJiRVx5bpO9h\nGCr/ir8TFf4OHweznOR9y/hK1HTpX5QkcFox771oL6/wt01c/n178ihIx3hV83eMULWymIGLh694\nwe5Qm9qF81v+/uG9Cz9kskpK1VpJ888rht43NjusVPO/DgPm7MIeKEwlH5XQ9m7kmjUbs8SdZ8Tp\nV+HfDbAydqGgqUk1/yjUSmQ/nJQeSRDIsp5KaT/UmP87jx+7ZSIwTRWBnAXzVBM/lYOIA4emwwFx\nKZvkkdQ75nQDTx5/GTcYrEBLm3JgPpw5RGRjrgVmxGqQXxEo5b2PogGuMYqgJ616ORnllcfsQTyu\n+WuG0pRdQz11qvnrhg9YNEBP3q/7Ysq/+26ExUFAIRC3Vj1xYGmekC4bm0whybgSLHJ9VZzmKvw1\nQvXSA/LM0lr8HZcDPdWaf6NcTP1s71k18PPBoZwrWQ+9VbPSw6PMyzyf0XspEEgXKBIcxYengn7N\nWj3L51GFf0mfoGQLPQQ1NsQPnKPETlSYv8ZThAJThhWG+Wd5fxEZIaWaaiuyBaqwUYS0pnfQPyhs\nHx9/WR/xm7DP82oSfG4L4yQpimPORivTylCq6RUKnxbpAIbDhQl/y/oH/doDPs7PDy4U5PtCNxOn\nTi7Mi25d0BvDIEDD77mQzHUcMOZr6xdQMjR6P4XqeUMVgLIKdd2cnQhXmLY2jpPDC2oud8qpd4qj\nMl9OYpkkOkBPVBMBgDEvHj12LUdz31RBaI0W1g8DNHhL+zzPZ0gCGb35jqQ9WP1QfuvLv18wf2L7\nsOY5HijNs1oD4wDNCqqbW62dgi1HIGccpqO9E6PUbrBlVO/kJuvMkhUC9QMEwqHLHKeo9EgX/ppe\no4WwhqEwlxAo2jV5BLO+P47QNsst1FZtzE4eLMkNO6utq0+8FEUi6LwiWE6ikINRFfVGXd+Tn0IO\n2t7ZWgoFzRREZTCZPFMPQs2pMx30oPDPOtmfS/QIX0vCl1UQr84AqpzrSqooLQqDSBWigIyDEDo4\n5cNB4Cerdb2C6MFFcVIbyBzuZDnoZ08eK+yjvoZklm/pi/RPHb4xkQX43rSXVvi3mP9pUdgH5uU3\nTSG7oD7dOtaJENDlE5aY4LmCyv1XOK56GNz5o6XuIgnlG9FWunXBSNooQyWm+ZPwN4dco4UVC0XS\nSIiArHP3d7DwccP8NZFXMM2qJ/+DzlcV5KKCUPq2Cibfsn2e3Gg0KGnBi7NjjJapcEw3uBOYHLaq\nXb/56CvyDlYTEo/eerMI/8UFFzv0jjuZIod+giaGMxhQhT+iCY/5WOCJhd+JYssWwOZ4PlByH+n4\nlB65ZhqzQhHq8I3J3p1FIINgH7bSxgMCCdeIFSFo1kwNRPP3kgWqiTmjE6hLq2bp/ANSgwIu/C1P\njioSGsCIaBGqEcr2cbbW0A32nm199SWyeZGk6SUZnQt/S60MmTcaX8CKeRTYBx6Q10eHW8ySV81f\nxsyav0fHBtt7li9JNGtn+6w4OxNYymCljHE+IOXbEhgYavRAI+FV+FtMjPXF5c31pe7hldaCWMMx\nQBliHJvzTcz/OTXniavwd4xw7t2jD7jmnxFxWms8tAh/wvxVCwDlmonBtWO9wIRCNCioWxdjNWjU\naZIDKoeInDOuw4BReNiqsZ0Wx5ctWlOiQ5EdMzbMvy95W8Ca9ThvNP+UmqjKnNEPIpgDY/7qZMuW\n8RRw4fGE/CTqOOfNHo3nXK4v+Hy2TQcAfd9bDMWXhQef6AB98uiRwD4EG5DwmcSyYXrrMM8CqTgs\nMiSnt6oycHZxr2DQBHUZUSAv0PiQMmZJf0GWgG7aKrdSg/mnGMzUt1q4pvnXh/eoEFbwgCeIf2Ix\nvwRFAuv4kDGKwFXYRyPIgcJcKmuuPnyUmeV+KiPiEhWZDqd+MOFtifVihyTY9ipOarOSg9fN1YAp\nE84Cowz9LPOjqTgy+o7IEaHMliVeyxSTAcX8VdAH8YN4ny0TqbyniBXT8dzeiTKoxunMWUvQzLLs\nJwpmabj/D/ZOdBNe3miOr0D9E2tM+p1F2QCKcsAR7u9Fe3mFv2JzKpQXD4RRAbywaSxm5MmEannh\nJc1wcrPTs8bayxyjp3fQAhBOewSutSrSmjEO7lxckBAoa6YFVjVUPM4MaWwaS+wWYIXU1XnaD3CH\nkrIxJtMwixXjjkXehF03IEpFJndIS/8oZQD379oKZ2cxZ6NXKFq3zrdhmKD+EIOqYmepM965rHn+\nGRFXl49wTZi/0vaMGz+O0GAr7fFhnl3zV7M81T6XiMI0STjJ/WTM+k7WxQ7BMmbIO4GN2VlGIjAD\nwT6ijfZqjYn+X67T9ec5lwBgPpybJaoWS2HILH4oZ/VgqScoCKRZLEuFm3TNAMCynMzPVN6NCP+l\njVYOVGEK8DxF+v5mw/zNEStJABd0KIFpq5AW9DARgakOTviaCBClQxUCmT8NuDIKZ3ZO/xpW8TP5\nO/G4HaVSOpSWYmHPlX0ie3mcqmcGZPT9aPOshACHd2AIAMBFkzyjgH53feNZXy0wVMaRNL0JgjmB\n++Qp3P/f/+4X8Zu/8N/iRbeXWvhX2O2qmj8wiYmpi6WwHAAO21etNmWvjxtlQQMSAUiaf4s7enm5\niMtbZb4smOby7EXM90qzNm3GBSdQ6omWfjqmeKo2bO387IaJhEe5fhhGD3KRuUnGIPFUB11/QGdQ\niWc8BTjHimo+Nb2VA9t00znP3Nk+o1ghAEVOh2ib5MlVJ38r8E4IuLq6xBJ60vyFW61Qkmr+geiH\n87nDX3rwV5x+0Zano6VYaLVJpVGqMDdWFx3Iyupy4e/v0DTwzgvQGANFlY/m/c1nZz6PlbBhzLoW\nPvr+hkHWtvoa2IpR/4X1XYT/ymNR2EfeH/wz0/wnWV9N/6LCPhUuXsasVrZq0Z7bR3wVXefrGOW9\nj7o+mb8v68r6R4QEhX2CWOIMq6ToKRWyPL/rRwTaEzED83xEJ8qPUZ2l78WS3mL+C1Te0Po4UREf\n8/+oFahJEd1yTakzh/n//Mu/jV/95d/Hi24vt/CHJ4das6dvnmdNj+uMiKI1Jqz00gBfpHriq6lc\nHL4dUj4himOo3JMXatF6HmnAx5oxG7eYHL4qaJaTZZUsz679CKzFKZsGhKmrFlwHPMlnA1kDIvz7\nNrdJzkiiLd8aZkz0VtFQ9d+GGYMXeg371M7PUpik1xq8ZA2kmMyqutFIUnQGQzwRaGJY3NnMOHTf\nj6ZN6T0Ph2PByeHpAZJw/zPEhEfGMPZF24sCL/CBtzpktP9OQiWoAUl/oHMma6xLvTtT9ZAODs0o\n2yfmBbPku/c+NsFgUOe1PIO0ZcXOjcacfZOf1hNYudD3d7JSgplYKHrg0FzHjJAXsQ59fRkGvirs\nE4wRZv4Q6YMJ/8wH2Wq5p5QEUA6ysj7t4MiemK/i9BvkKnMdSPPX66ImNkxuTakfhuZ0mBrNP+cC\nI8GpwLqeuRa1+Rh1rhefY8P89X2DqZ6yflNn8GjOwcqNvsj2kgt/F+JKx4rE7nBqGAlV3eQy98Zg\ngEA5tBBuJdS7XF+f7kVrFY7zI/H8rxmHg9AKxaHKzsVlKZqTbXb9XE1ltmSyWygqPLJp1iNCAyUM\nfefX6ULvB5sr+2wuWvApuMPQYB89QKGQgOLfJDwaaKNyfkpkZ+pFqJNPIkkqZADIrxetJ4TCWl8R\ncCWHssE+qCGevusqqyPkFcfziwpSichG8y3CugjCYSqpLzgwSoV8oRTuaP5VkRA9yOSzEDYCSRk8\n5XAqX3Yk1OxQxorx7NwsHvXFlOs8B34goaQxC8gZB7Es94K8lmVBZcXo5woDCcSX6QCNonAsEqQU\nsaKnsei6Aco6zCHiFDxjqGv+kPfmsTX89yl2lSCOeUWvvjnyozmcBrtPS/WMooVzhHsfk2n+Rt4w\nBpYf8KnrnHqLKKm4aZ5J87cEkQEGQdlcZ2K7QfunWn6qIFgA6CWoc0HEX/3Ya/j0H34dL7q9tMJf\nPfW2WLI6gYFZhL8Lar5OeeR6ui/mjAvwEIxSYi85bU41PaWPygJeQ8Djdzxi1YW/Ohd9c97e3opm\nXZuVJ/kl0HNOmSwMFh55QTc67GOaf69mtfNE+qHOZx5zxjwV/PvW5obSCNABClDVKOmnamHsMFTK\nK1BgtoAVXT/Z5teThWGfW6HDjk++wxyDV01R9kKPdVgr6oaCa6OqQS/QQzBjFIHi9E+g7ztELAaV\nVJg/3GIEaHNTPVYTWvKeetHyy7sr9+xJWzYLITLsE0S4ZszTOZQWWgnXhu1jsI/CFsi+tvXwphKj\ny7JUmLVpqaFeSwXz1/cSvAyh9K/rBnNY6oFQnuVj1s/cHyLWjqW78JQWEYWlVOPvwDiLb06xfLjm\nf1ILglNp6HXBMXW1hlPsqZyiMKiEYaPwS8SKmEr9hEL1lFQfGgwZPAahvI/aClGqMwArKFSgIMk2\nS7CPHrKq3w9db5Hwv3t+wBcuDnjR7aUV/k71LP826loG5rnG/JHdQnBB5trMEoopG7OnP1jJPC33\nrTX/IM/PiLh8+8tyz4B58jD9VQOKpI83p5IgjZOIAQQlkeaz0AbW8PFVNuIwSaoDMnsVh1Ynacju\n+M5RYBEAw1mpr7qQw9AK0Ci2rHOjwloPp+xQly5qZeyUcRStqYYNovWv04jhrszR933Lh02rvhYp\nX7N9/MCD8bgdh56ENcOHW2/Wjm/kmEr+HPMBZUsKINYOH3iQtaNCTAUmfMyp22j+/TiaFaPvs+vU\nt1HDEf08+UGBLeyjzBJPz+Hv5fyi0BcNtgMx0XKZMz202zz4leVmlo2SIZKzcIxQ4HEIZW7EBxQ7\nDwSU9WAcd/gBa+8PGTEy5i++mL4mZlRaNPnrNAhLD7yUgt1fE//F1NHY+ADMYCgtKGQUIlYUa8FK\nhJpioZZbV/eFYVm9f3blx4S/OXdpf/YDosBm/e0tRmHQvcj2TMI/hPAwhPCLIYTPyc8Hd1z3t0II\nXwkh/DfP8ryvpal2a+wM3Zk5Y+7rl8ZOI31pDvs0mr/yxEXzVNpcaF6wV0CKeCwRq2EtuUMKJONU\nNXO8SXbMmOs+rNEXf3tIxVVzlrhmNoyHDYOk07q+cEezHkTO2siYj/eQsOA2qmDyZyrso/1r6a16\n2DLtMSC441pZFimaIHTYxw+2J1Jk/Nv/2LcbgKROyZ6Cx5wHny1fDEjz7yTwyBlOGaPgyFzgBSha\ntTtJieeP4gvSwyA0zA1VHDJI8xfNuFwnmn8/mhVjTvjkc7x479GPbhnVCoZTdSM8FUdWBhAyDhcP\nEPPiid1Wf3+LsHbamAUfi0ebG+yDIBTOiBxL/7pOs7LWh5MpA5JKWtdERQm1Q6mBsKw6mCtV0+TM\nOF1vLYRSImjlM9P8O4d4dP13aaP8aD9UEdD1rLV0tczq3iELuMPe4gsyMeN0vWRnCKqFkKJGSEfP\nitoN0PrQwytvY374Fbzo9qya/08A+GzO+bsAfBZ3V+j69wD82Wd81tfUTKuTfxtGm4GpfwodLtSC\nTavrKI/aucuqLevCL59bUE8IJhSuNHfKKic8Fqya1XP1BXN7pVWjPGMkUPKMlL4Qfgtf/BqBqXCA\n8uhZuEY131UQ5sJysbGIQCmY/9Kku641/5bqWcVLoM5TXuoJQ/5eTGvBhBmfDyGgk/tdifA/Pzsa\npVNz6aiT0g6yPS1OnyM1DMzUzy78Mxwa1Pd8Als7pZ1C7X+x4urR+1Ge6xu56xn2EczfHNKcxqG3\ne/NYOsudIzx/czAqbCfO60ooFeE1XdxDwgkn0UoTPM3zuurhDRtnWV9kxcBhJADoUNhd2u+IVQ4y\nh3Na6/c29JW1wodJim7tLKFo5gErgigGjPkPvTKXXPnxQkywz5Tyag5VoVIyz78cyMpacqjKn0mK\ngDD8Woeva/7lbweRHx5ZTPuTodryq1kmfUdUTygs62vmOgZki4x4ce1Zhf8nAXxGfv8MgB/duyjn\n/FkA7zzjs76mZg5fXeDyeVyz5dcxAcfwkGk8jmtrOtsiUNT5IwuhEdQGJYmwWUPApUTAxhWm4ZgJ\nSFrm1akUDjFBo3BLk6oWQEXFU4dc4UwXhxxnYmRqJh8SA2lWGQHIGd00VVpwpM2FnI0No98B7pMo\nB0W92SOCRY6epAiIVvJSto5uuk7GpKUs585TB28iRCmwzYQ/MYCKQPGiIwYlWPZI0ZZJsPKYtZmj\ncjNm4pTbmMvF4zARPKQbPpm2rJqiQlCcdiAiF6qiCqUQbW0FuDVX8vhwnqIylsPZAQkLbkTIag0I\nAFjl8PDDRMfomLX7j0pTi6yCfYbOrR1m+yyu+adG8/e8U719nun9e6ZPh2wHLVpvPomt8zQiQ9In\nWYBUilEEvVtZqdPSk77+dU4tyIusgVMsCepSXptD1v+2a3KE8VybHFmpwI7BPj085kDWzDhSLYZk\nSuWLbM8q/F/LOX8eAOTn+5+9S8+nWXZGNXntZfuJzS9NEVvf7OVnGxWr+fg1qlJhH6N6iinYwTV/\ny40u/2M2TUC2ZFBabaw9ULyf5IgkJ11qNMekbIzgKQzKo7M5P2MG+sGLWajwGMepgn0Caf4LOcjL\nz9IXz46qjlhnWURwhKNAZ5TqoBIeMqabUDZVH9yZbQWxZZ7NYUaYszleTbNzP4e+v3l0hzs7UyMW\n05YLlNCuB8XJUc1FEOckH3jDNG3ZPuIHWIPnc5nECrHEfGhwZ+mdpxPQyFPh+UcP0rOUCMMglhu9\nPxmjYv7G82/pyQb7RCoyUnL7ZM11g5ICW9dXzfbJ9v6csVaybJmfozrw3FFd3ulK1gQsIHKJzjxT\nLZz9YLpuNKY4dn2hrJLm3wmssqf5e8oHggB1f66e70qFvx5sGiTp/gfX/B32JN9dUNqvKzVmBU4T\nWdLJ5vRFtnet4RtC+CUAe7yjv/S8OxNC+HEAPw4AH/nIR57pXhrFp4LLcOkVxo82TY+5uMYxl595\nwQpy+HIO/BBJeOg9VShEE1waPh8WALKxXct0f8P11ROsGGxxmWaWfKG7b0LwQ00cpUIda2G+KCZL\nC51D6gO8cAWskpekWcCCUxjl/ll9Zm493aEFaw0D1oJTpBgIWdRBrAeGaACghwr/IiA6OSxKcjzr\nqvzUvwcJD8d5VYiqP0ST+k3TDOAdgrp0rulArqCEeqyuxUk/UAsQoAgtjzotW6zkw6lTUozCya81\na6XREqxS4dMO+2hdCk95XOiLHRYLQEyk0WaxEI1NFnRvbN+ftp7YZyehOXZD8WncNu/PMH/0GEA5\nmNSyBIy77/RWt9wqzn3OGPoJwFuNoBflizF/2X36/jqzIhhWGRFumFJLc0rPLH1bbf4iMhXXqd/H\n2A9NX9hPB7mXw55qmQzDiHBV8/zncXK2FFn/L7K9q/DPOf/QXd+FEL4QQvhAzvnzIYQPAPi9Z+lM\nzvnTAD4NAG+88cYzjb7AGGTyqgYnQiHktWYMQK/zzwB4jnJZMJ6Pv6Z9+UtXjN1pZIulIQZCDKJl\naoCZP+v68jGW4BlCHfN3jdvHo9doEqvoedAl3awHp7mWsyCZVTQmpT06Jt53BSdXnnhYObDGLRDA\nc8PUVDcN+9f5qxd/FHzXsGDaiOoMvBbhPwTKgWIcetizNhs5ryKQWLOrA6PmwwFF+Iv5rxZeXnAT\nJnlPebtu6NCp3onNv495mGfS9sqYRqkxzFr1NA42j3tCqeXRe179srZ0vszxmvXAc82fA6MyCqto\nSyhgzLoEuhlsF+j9CS8+pWH3/Sml8SYMmLVOMIpD1ZQqOfAs2rby2dRO5DFpkBdh/nHLsDFrQIV/\nlxDyrcFKANAPE9IjhwWN8ZQ1CI0ptSuu9fDMKzqtKgOB12RtqWXCVrzJEasSCMSgcI7DffFS2U6l\njdPRlamq2h28AAAgAElEQVTQvSea/7PCPj8P4FPy+6cA/Nwz3u+5NaOQhVpwOca74AQ3jc1cM7ii\ntJRLMrMlFI2qqzR/5vyWZliwhpMHTxnBjjvjYcM1/yePtJaACMNWy6HvOFzeIYpky8lSBpCZ75W8\nJJWDpXTm+arN3khzoU5mZ0KJ5siwjwoyS19ba44KZDim7ZrjKNRH0/yDY8NqdSiWbvBEC/sgmNWn\nY+ao5pHKBW40f6Uhrp46mDnwPGY/kB2CsvQVw0TrQbS9rjMfkOVbkkjzuHp6B3ZeO+bv64bH0iVP\nf7DSVk5YcKtrG77uTgqZmRVTj4UtS3dKd85Tl76wVcsHrUJytxhqWIWCmTS1StG46wOvjNnX4pTq\nIK8Ar1dgmD/5PhhW4cMFKHCTBn5VpAWzTEgRwGLQY8zZq+9ZVD7kPYvyRA7pvcBMr4utwr8H1EpV\nWHCebZ5P+IMh/H8awA+HED4H4Ifl3wghvBFC+Bm9KITw3wP4GwB+MITw2yGEf+wZn/uurWgP5IjV\nF7S6cPTgERJwxHwAlOqZrHB5n+p8OA451M9JoTMt+GSbDf5sgpx00T2Woi3R+rjFN00jJW3NNQZn\nH7lwRPWZWTEZGBKnlxbYQISxmb2rB7m4kPCkX3X/sm861eYp1cEiWpPBPgjGIAGASdJN3GBEyiep\n+KRpkFVbdSd9CxsAgk2TUDdnqgA53aTppIMF/ZX7rri1De8v1JhWxjZSqEstPNUeXdAMk2v+eohO\nlAZZBevxeGZjWaBR5LX/YgXDbOzwhVX3AsT/ZOtssbGkHIkKqWMtPzVavYV9ALeAIzn4T2a5Beof\nRz+L5o/eLWIIfVPzLR2O0gctau4wisF28l76VKd3CBleaY6gUIWC9PBOGoSGCISyXof5QILZMfXK\n4UsKg1lOa7Y9n1HWsO6naVKHNM9fcziBHeuiCIyT909aTRLw+t0vsr0r7PO0lnP+EoAf3Pn8VwD8\nGP37Tz3Lc76eptpRMppirbXGFuM1c16wanmJmq8k9yeMOJkJmAHDkfl6wx1jWQYroud5V815Y5aX\n759c3wDnZJ3ERuiKGARY83fe8RKYxcCOLGL7EASSAmf1dFZJtfh5QTfWk2thdRxCcbQpsyEhnOpN\nt6nhKn2eJO7gGmOVG4YdyOqvYc3OqaceNepQScataHsBGVELkagWR5aSassczMcHb7kOzTsJ1kfT\nbqfZD27Z+qNQ+UqOnCjXiSBcHf9lobSBfZBxi86sAYvQjkAOyYgDbNXGQIqJCf+yHnTzs2bNawkA\nhhRJaNL6yoDDNuqQLve7Ib+VWgiWWnxy4d+OuQpsy+suMSNuPsvok34mey91RDwQuFbyXZV5IMYa\n/OBmX5YSHlJeLRhvFUtMr5vnM4RbCg4EWU67sI9agSM0yMsjnzufe/zBYPt8wzZzgMm/mS4GiPCH\nC7g2oIophQsSbtEj4WQ5xp0eVod6q5lfXqYkOaMYg3LvTLlzsoWGasUuc/jqQrcEdCDnqWpmDPvE\nStC3mGzZEO6/SKFDyItgnpE2hDsMQ95i/g77QMZMFlSuhXWXXPM/hc7hANXoqc/HYxEMNyT8dZMo\n5KRCWYNkWuHI6R10HlQIxLyaZWNzYwFPa3Ugm5ObLCwes1uN7JcQ2GcaTLDqPcdu8ufK4ppHF4Q5\nxEq4uu8kVmtWD5OQM4auDoJy4bVgsffnh+Opuc5KQ6oVCs6TI/PddfvCfwfz13WYK/hRMHV59uFw\nRp87SaHcs06yZjV8SflRP0dF9RT4UuemHwdaX6WvRdvWd9emn0A1z6lZ/wqveT7/cl1/kBoZlfKD\n5p1QGghVBOaJlKRyfZccXrtFb319ke3lFv5wYWELyIKEiM4FbDT/COfhL0g4ocPt5WymtqZEcD5z\no/mnARGq+TfCPy+1Zq3C/1QXRpd1TgeXH14WLZjDHZq/OHJJuBrzRfBNpVy2lLuUm4NR2Q4E7wBw\nOKjhOSstECgh8F7xqLFMQqygjsN5qZ96jcGqhQVogi6FWVyAbbTlTEFCDexjxTYi+RsI5y2Yf2/j\ncFZJ+V7XjY3FWF3OkDHh3/d2YOp6mPvOnPAGDxHVc/v+NDK2CUSjhHvD0Nd9KV1DRwFCMQRzkluO\nqPb9MazYwD5jlyiZXUfz6jz19mDkMRnmL8VsDgL7MNuren9Q5yux8iotf8utH+wz0ayT1gZQn0RG\n108+z0j1PKsSYcrPihNh/r1U/ivHiGv+w+FgSeD0WvMdmjUVnIqqzv9+JItI312kSODum5r/szTG\nsIEtR11ZPIAIX9MKGsx/LY6pWwzAbWdOSU2hbEwVeYm3hvH2RMGE3NO1lb3EW9cnT1cMAL3WQK2y\nj8r4KofqFsu0NLysGWcX/soM8UjShlKoi3JdPYFYA4Eo7GP1YuGCxRxtMdlcVv0jgal/c//iFbmu\nd9jHkrXpM/cw/7X+jO7pDl8RrJJfiKOadW4qAoD12Z/H79Cci5XzM8h7i7bhFUrqkkTtIpoV05HG\nDUAyurpQcuaL93ExqHK19Byb+AsSHIkOuIW0UZ5Lt+hYkZADquu9f+RTMj8H3AekQXo679oXj+dY\n3OGbtz4bU0Tk/bnm78qPQjysiFiwlexnpaICGoVfrAPPZZSqOWUns/b9lpQfpXR6kJcQFI5nclAo\nxMPMNnZIuyIQ8or+cIRFGwMIean2sY71RbeXVvjrZm/zf+uAA9zMT6zxqLlrL6+86GuMeLBMnhhM\nHb4NPn8SgT0N6tThdLaE+eviIpz1WjeMWie6qHccvg77JIoMrNP1WqZIctCWaGV/7cE2HGvBrjmm\nDMpqWMMG5nwjzYcDugDZiHIvZjG4wHTL5OLiPj3X+6yOa34mC1xzGGY/UOogHneSBtE0neGxPfAS\nQQ7uWJQxN8K/DvISgZl694fIGuskP9CKYEwoE/6W750Px72snpSCAsBkbJO6j2o1AUU5MNihOSS6\nljYJYqsoS6kf9g8n0lw9OMqbrzm3YCJWDN1o42vprTXVk6J5obBnRhpq+mdcYXWxdU+NUtWtjKP4\nJErmVh8HO5kzNMOu9301C2u1PW8kD9mf8/m5WZY+f7Dn6nsy351YHMMkldAocA50X36XL7K9xMI/\n1A6i6FgpUG8kZNBLU6qmwiou/Mc1OuwTarxa8VPV6A+HCxI8kGfqz9qhajlRaMMAnvhraTD18pkK\nEKoXG2pzNquWTxqNUgIjLX5evOU7X4Uhe2zD0goZO/BoGZHGBajmCOtfhbWKDqWa1NnFhd3GSllC\nMH/VtKPP22rbZseE5zErK4WhIIQKv03VmBnSaoR/Qx1O4ktg513fJZsb0/xjMh+QQWKU50bvGVho\nYgv7LIRFj4ct26QdSwqhKvpS7iNjsfVFsKJalgRNRdKY/XDylMRm/UYX/1XUrowjYcUgjC47PCqL\nM9u7MuZZXqoMs2ObUgElWSLgwn8YpwoKLYGPYfeQZT8D7xNtIQODWCtcAhIomVojlobtU5rDlNGF\nv6Rt6KUSms4zM+Da+XuR7eUW/tgxHS09QKk3CpQN3WJ1ajFo1OIVZpzwqOGJR9pIZYGqo+j87L7T\nFGVFJNKQT8Qs0Q13a4tP7qmYLlHdQiNcY2jZGE7r1Lq+ddSoa85lnCtaFg9rjilvoyrv0hz5INNr\nh653Zzhp/uokzaQ5nh1c+DNbhDX/Pvb0eY0ZK4+e0+5adaQNrFU7U3nDR2zxcINKZMsYbCcFZ/g9\nTymZIDyF4vjXHO7MfHHYB3bPChYzoeRz4tBUqYVc9dE0cMb8E9R/dUr1e1aNVmGLgtnX728aR4J9\nKFsn0WX1+1695PADrfi9XPNPlMl0N7ZBNP8af3fY0+pvkyKiwjnL4VkSG5amsE+Mfs8TBbopK26v\nWhtQrI2D5sBqLSdhEDkUR0gDxYGotXpCsT5KzEG2eyoDTmWN3utFt5dW+GswRuuUZE1PNxLoxHZH\npZt95e87zOutLT7mxgOF0gi4ULh378LpZnLvYPgxOXwBWpRynfxBr+mHTdBvYZ8uJGKgbDHjWvOn\nxUWa2dpot7z4Q6ai51T2EiiBSwClyTBdkKiCw1jxsCtHoG46+ZuD1J8t885sH8fTlXanDr21ER7b\nqF/PZ6TvuDb1t9ZOzEBMKvwbhlNDv02iOGiRldLHZHj6CXWem6qwCTO+oFpqLZRYEIacCfbJmI9N\nRbodK6aPfsDZdfK1lvFcdnxKqnCUVBV6eLPGrAFTTvVUS5X7EGjMEQtZO5ySpNbCV3pXFaySPbCK\nFY5xmBCyU4M7KTAPwBSBGIkVh1StD2dVad/p8IQGZfEz5X1KGpWKkNH4TCKC5QNTwoPW6wU8dgJo\nYbNvCv+vu6l51tIld6mepPl7tR3HFLUdKM1slmfoglIKqAr184v7LqAUogmuoSkckFYW/tI3oXyN\nY73QsW5hH03lAGwX9R4bRpulK0Cu0lwADWyQWeDVmv/YbIoQts7FcWDOe435F82dNlNw6qUyVkwb\nJAdkmSO2dup7cuS1Ystt1kau0cpjKt+7FquCWs/DXteTRgNrBSrS/LsY7JAq2l7NeS9+igVRBeEu\nrOL4Nx/KS+WInKu5dsyaxhJ7pNhoo+qwNM2forlJIwWAkSCK1nKzCmLNeuA+GPwomn9n5ICSIbZN\nX6ER2gzRcTyOVmKr2D7HmepqrKVwTq7XR4zRE9lhH/axAFDeJ+tqObDYiWvjJMu5aP6lrST81do5\nhVIHITDSEChCnTX/b8I+X1/LpCkZlznUwrxy6sAngnOCA7UgPAZYXdEcQkVd7PoRIS+4FbrgcRpJ\no1Mnsmp6i9EKi8O3dkrrJjYtRzdtQLWoSz87y7HDqWAtoAg1511bKwj5M4YNQvai5y3+rbnxOfd/\nC5/140gpMWoqY8tjBxzr3wQJKYwkUIc9h/7eGUA8ZtfKWfM3J7dBJfWBp4LZDzzRbrsa6krC0uAD\nKiFgkL+/DQMJMj8kyme1Jrk2B1lJi1BDUwb7YEU3OBZdvT/SXLuUPAe+wT7lu6FvyySG/cNbPitx\nGnzQ1srFJFaxzru/E8f8u8ZKWQOVyASldNaDDKs5fAMyurFmOAVkjPNZNcfDMDdsnxWxg+0TDtSq\nrEDre43560He+g2tf1z1Luj86Z4NRkWtFAH4dS2TTMfxottLKfy18EcAm++NdkSbPcLzdZgjVWAc\nxuEOKWGYFV8sgstgJIkc1c059X11ugMetBWRaRP7Yjs1+PLc1DBNYCqZQgxeMnAhpxFHwJpQWHnR\n+uI3zFK/o8Wd4Nr22kAg/Saxlf/tKQr+Oh/sIOXnqsOWmTnleUVweSnLJmPmPFX30dKQdm1ookYF\n86+1/Jqbzc8DUPDXhsmk62bQgCLLHU8J28zJVwq6+JiducRjVhpylce9EUpFs/b3sgYSNF1ROPYg\nTW1d19maOTWw3TQ1WjTdwzX/oyfwo8hTE+oE2xwPDNuxn8kTDHJiPqCFkjxlBFtAPuaAeWwOrAzM\nZxeIZCkO41AJV9P8+R3vwGt78xdztnfZBjnqPNjhlKnMq7EGo8NGjWUOwJLlAZ4bSe/1otvLKfxv\nJZ3smtHFOgCEIw+1lcAh1xQAcsbRQjgMgxWYcIevvLi+mJ6q+Y+dn+PmUDNnF9EKM+GsjfCfWhMX\nwRKF24HQ9R5pizqystWCWcP2QzC7OWtmb41/cwKx8rflumE8IOUTza0LXeNXzwfDv7kPeywLwIW/\n9UE1f5nMQ69ZIcu/Gbc32Afs8BXMv9IwSZvMOh+1wzcZn7y2GJWtYkVaomRQFQEClPWkeYrK/VQw\neXpptjRc225gO6N67lluQEjlfXNiNqD27fRp8MRnjQLkEIoe3uwULffsR0pSh0TzxbCiRGifndtz\nUwO7LaFkG9UD7y6GWuvn4MC2kDOmeba/07HMpPkXWqc7VBdRBGIMBvvovfT+bTEXnr+4+lpoD9ny\ne8322cA+IWAcWPP3tar3dMvONf/gj3hh7eUU/ktJJ1s0/4aRQrCPti67dqWCUDF81paP8xlSp07Y\nUFXd6kctuq2HR6xOd8AdYhXEANaWa+HfN5g/w1PFXF4w9AMljmoxdeYRNw7fCvap/SEVWySXEH+e\nG3P4HmYw1S2ixjIjSjH51LkrqxbUsaIy8rO7rBZAnTFzkkpcYQ/zB2PqteZfvpcxkZ8j7mz4FMI2\njYAyeRSK04CirkfkuZZ+d+O+5u8BTwwz7WnBnLtf30Wtkeq9PdvqnubfW63ZtlKZ5lIy5YTmaBW/\nRDfOnvcffXU4KZVY5/r8/r2d/nmm1cra3nW+eqbPenxumYzjAVqxTT8bpmOl4KSYSLhq9bhQC/X2\nwAlbrVyv0zTSLbym/atSOrexL4hWNIn3Z+3kV4dvqO77ottLKfwvr0rZxJCz1UltnZrVQoyRFr0I\n70QZHqXdu3fPognbYs79PCOS0GT6KAc8lWfz4gnQBB+cqRCgSkYMq5jQK0I9daNDQXsOXxLIlcNX\nf2Zy+O46PwOGvsmrLt9N01zFLHAxCw2uGeajvYPyty3bpxUKshFMgDWavzBcnH64ZW4wA4VptQyp\nLLRhQfOqY+7aKk0KlQy1ttxJbd42uEzfXblfHYGszBebk0ZQ6Rz7WGB/b42sGI4A5zkEhG3VMJTM\nQXuoD7KarVKw6NANDmVUcRpu7Wi/Lh68z8fM8GPQmIqtz2lpaJcZnprF5oxSWozjAUz/jHlFN3hE\nuMJppiTJWgiNklH7GVrLidbjupryUuXj2uvfSnl8SAlUa7U8zxUBvc6VLrKQv6n5f33t6sljAOKs\nSft4dc2IIM1ftfRBMF267uG9h0h9ndJZvx8Oh1qbI+esOT/tQKk1f11sqvkrjNM3tLZEm0KFXgv7\ntFowB6LFHR7x3uJXtlF5ZsbQ15Gkag3187HSfBg+W5TdMUzGzQcY8/diFnuwz10O3+OZ5MDX94XG\nSSqaPz+HYyp0/p924HUh2IHl5nv5fhaHo95Tk4j5c0u/p2k2+qGV+rREfw3UVWnBfq3lXCL/R/s3\nBXNuAhjp/Q3TbL4m11zLmA6aHoKck7wPIlaENCCRBtTONVNt7+0If2UtqcO3/X7DvEFDwcXi9NYM\nxL440Bmqip3DKRGa0kUtUFIOKjaN92MDCbMikGGJ48xPtNbKykJidFM/JEaM82jft8w73p8cJMcw\n5ItqL6Xwf6KaP1zbbh13taDm/DOCdUoucU5W9cr9h+68bDT/eSLcMa+ykVwQApTIq4J93OpwVo84\nNyUU3qJyCQJQc7EbZo86hQfhWN1VsPNzu4lbqlrpU60FKyVwozkeDwX2UdpjJEEm/PI0TugH0vxN\nI9TAqIg92Icdvpz98CBRrWE3JYJbEzWmW8NaTG81/j5v+JjcyRdrgTlKJk4VSEM/kBXjc93PB6cf\nmv/Ck9TxGtB3yhWcakGofWSHpfQV63YsJDim8eBBRs37myXJmjmvmYKoh2rf1z4bOizdIS2Y//Ge\nHXicUkSVkLAz5qL56pi47rQ/hw+3zrj1xNRLbukFEf6c/dbXvz3e+4e8gXNSK/xt/upDQuefYR/1\nr9hBETubZ72G+1JqXMiaSST88eLbSyn8b28uAUA89TUjxTV/wkUJ9vHgpC1EczYdgSRh+urwle/H\n+cwFlyUlk3sKnKPUukrLjHD+MXGDuQ/Oo6dFI5tpHGcK8uoqQQg02iQv6nVHEDbflbEEY/W0B6iO\n2TZijsaHN153P5jloM/Tn61DGnDBZVk9heFiaZAP9RwuiM2BsqV62rPp4OeoTP4JlChejX61vDLy\ntTkcjdU100FGsM88ERRRH74F3qEo6pXeVdZ5krGQcGyD73QeN1YMvb9hmNxh2R7e06E4LPXw3lEu\nQuobthbDdrFi5pQ6xfWYKs0/b9/zgs4OxyrgijF/DYgMQOoKzMYMmxAD1X8QiEcpl6hhJZs/+8mW\n746StGZifqnPy74u/bPDKSAlVcTU2o8GVVbzVzl8RfNnkgD14UW1ZxL+IYSHIYRfDCF8Tn4+2Lnm\n4yGE/yGE8OshhP8lhPBPP8szv5p2fXldfsnA2DWJoMi5pC3FzhbD2mjpXO1m7hI0K6QFCYk2Np25\n06kVPPpsFRyV447wSQ/CEZpdqvHlGAj2kU2XpqnanK1ZuRCnOe4sfmVjlL+R+Wicn+0hZIFtg+Cv\nYM0R/lxkhNBRSlzWfLZU1NIfOUCbgJtSOGfBdGxgnypDI0ERO2OpBCZqQZgWPpDTZsw6w7qRTfOf\nZ3J+uhY8zUfb1FyYBqgT8JXvZSyN83N5ilDiokRPC9Ibp8mIBqfGQhgb2C5FH6dpzH1fwxH2fKqn\noHPYWGHad7eKdjB/cnNWmD+Nz3w2KxC7WvNPGZadludYD0C2OPbSJygbrHzmY+N5Vkuc6wr496xI\nANE0f7WGe8xHT1vi+1Pn2Q+ncZw3173I9qya/08A+GzO+bsAfFb+3bYnAP6ZnPP3AvgRAH8lhHB/\n57rn1q7I4duNY80OyKpdk+afHHzRhaCpZ9kJM8TgCy3UWsU8uvB3c7/8nTp8x7l2VgJidYg300tA\nivVB/GDti7N9ksA+w65Zzg413xA+R7VDroFFKiZUxDC1EY4yHyr81eHbQF3F+ZYwDUx79OcaW2QH\n/3az3OcwYkUamxz4d+RmbzUsHjPjvKCDw/qQEnoNgGqcqdNBqb4JIS+YpiOK87OGcwaCfbbKQKrW\nn1udDPvs0JMJ9gEfZCYIt7DFPM3oWthOtdKhFM1hzR/WR9H8YzTYg+dTC71rvnwARuMsffX+5fDV\n0VvdcZ4a4Zzs/lGULzu89XnNXLOSxE5069+e5STftfEwlsCwcf7r9wxLtfEhfepwlFrNej1A8Cgd\nThNf942u+QP4JIDPyO+fAfCj7QU55/8z5/w5+f13APwegFef8blPbaebUgs3AEiCybr2XK6poJfk\ngTB6nUYrdjRFE538ayxmuX47Twfa5HXBdl0IBxH+Ve6VkMyZ6Jkio33HfSrJqWDXRmQM86FOqPUU\nTJGFR5XegesaoA42iSF6vvRQX9eNcy08AuAO3ygmeLLEWzwnyhZhfBfYd/gCoi2j5D3nPnBKhBJQ\npH4ObMdsPwkzVm2Poa7YYZjq6FkVmPPZucMUyBgP5/BUFT4WJgCwwPSxMATi811TVJ/GwtKftcMR\nqH0D4+gO95a5hFTSDVhq85h2hXJHOXvaMa10+Jamws0PvDY7KY/lRIc/M8/cgbtu1ie/P32rjOHz\n/FSYP/P89WfeOsxbh2/5zinR1fuq+kfF3qUHqevQ94PLBJ0r8q1YkNwZWQgvXvY/s/B/Lef8eQCQ\nn+9/2sUhhD8OYADwf93x/Y+HEH4lhPArX/ziF7/uTl1JIfSQM7q+q0xjTVJVa3qdbW59wQrRJBKs\nY3SroWUldB2H8deav97zKCmLebN0nJtHBJs6jTyPjDqCYwMRlMLUu7CP9GGRAhKlX9hcV3HeVzWP\n6XCKwWAbW/zW96I5rgYbeMlGZTGEEKxua/XcTEU+Kv563YfKPMZWeHBudoeIPIFcjfnTmFvBymPu\nEwYZ86nRMLu5hvfm8wuHNijgaSLqb+v4bTX/qgIWa/6N0NsbS3FY1gdZ9f76AcMoVMXYHHimRSf6\nt86rH1BM1XXLDTKW/SIkbaTyirvZPswM2jDP8lb4lz5rzIx/ps/jfvDhVFM92XdRUzirQ3b1+3NF\nMW2JCQWhwFI6L0AhBHRdTzLBFYdynfvkLu45IPINAfuEEH4phPC/7vz3ya/lQSGEDwD4zwD8uZz3\neUw550/nnN/IOb/x6qtfv3Fwc1WCvGIuPOzaIy/9oYU49L3piobPi8DqiKY4suavsI9stLJxttQ+\nwIX6JCmLK80/cXoGETRCCbUydrrQY6R+lkXdz3PFErAFvPrf7lHYdqmezT2AAoF0vZiyaLSyWBea\njsTcYY1rGtjhRbDBHuxjQV57mj/zr0n4twIJzPDYHhiBYB/D/GlFDl2Pea41f0Wm4zCBmSXzQRy+\nIUmQl9yv76pkYzy/Cx1O5d7bw7vGkv0zu64ShA0EQmPuh4ly+Ch8WAcTqf+iQ6wUFqOt9g7bhea9\nLI3m79Gq3k9j++zx/FEznNZ2zKA05NTnu+J2bG2awzdu+sTX8VrYY/sk6lub1ZPvAwBhBUaND9E5\n7QdBFjwOQeelnb+Lhy7zeK++qNa92wU55x+667sQwhdCCB/IOX9ehPvv3XHdBYBfAPCTOef/8evu\n7VfZbiXCF7mkP2DTTGGcKgS+o8pL8v0om7+n6FTW/BFUw5TFUXHL281eoiW1eHWont15BKUFhnC2\nUXJuhc7SQi9IGLGim4+WRKw8s9WC9wUhh+m3Cat44fUxoev3o6SBOlq5CwwbuPAoAvJJ2cS8qRWf\nbzQp7gNrSMyQcVhrGzVZcujvjZk2cqPt1e9kxNhPAB4R00oC8IahBLbJfcZptOdzwFrqvA5ry/Yp\naThYgOxj6m0f2+Ci8tn2kGDhNUxTyQ57y87rWvibFt1FBNk6DPsMLPybfrLDkpspRWQl15p/+Vml\n3dh1vrKF5BYC15jWz0r/tgetZeuk/vHh8jTlx6vvbaFCvo/en4NKQ17Q95NY7O1aKH9zCgmT3OPB\nw/vA7zhN/UW3Z4V9fh7Ap+T3TwH4ufaCEMIA4L8C8J/mnP/GMz7vq2o3N7cAykR3vbID9h1EQKHD\nWa1fw/yL84VzlKuQrul18h0nGLvDwacadH3wJHNCG+xDScESqORjDJti6NM4WKbJ8sza/K3M6l0I\nhMxqu4df18UOMdVz48chKoGckuuUrHEN07QDiW2LsXBLjVBuGTL6nBOzRSoctZ6P8rv2eevn4ANt\nGCfMxvapfUU1s6REf9bMI7cE7/JftBDWnuZfYcnQ4D+2Yvx6d9jqWFjz7z1Ow7TlWvirZh1j/f4M\n9iGqrsNpet2+5h/pELPspDtWWD1mdnLX6wVo9p9BVTXm7xCSwLjYMpC4/wFM51Xlxy5zC4b3fEP1\ntMBjqlEAACAASURBVJZR1ROOkPTSFNG9tVJJ8784o/7tgiPPtT2r8P9pAD8cQvgcgB+WfyOE8EYI\n4Wfkmn8KwD8E4J8NIfwd+e/jz/jcp7bTqQj/sJaFWy2WHY99T3VmPVtmeYkDBShp44VQZwBsApQU\nehEsVYU6L/xxHDdpYNVMB4pwVc2s73qKICxwTuq6Svi3zq1KIFHiqFp4qEa/XfxD11luGI4E1Vbl\nKYrRzGSGDeZh8sWvQ1c4ALUjUFu3wfxbJ6nDBq32Xvk5dul9HCEqnxHVcxwGe+86N5qOG6gFU8kW\nqWO+K4VAC2HVsE+H7furMf+tRcbpHbYHWa1cjE2sS3140yEUu6owkD53qtZjbd2yz0U6Vu5FyoUX\nFdrCdjpWvefTaJfM1FsbCKvV/B324fXvvWRmm+4v7Mxzt6PwVeNoDmStvqe1jbtxqv6m9U3w/pw6\nokRvt8Rzb+8K+zyt5Zy/BOAHdz7/FQA/Jr//NQB/7Vme87W221s9ZYsWXTR/EbyhXixACdTRza3O\nH03gxjnKtVU+hMyf+4Iv39WCMDRBNkDJvWKVktTRO/giKJlCxSwnx3QZXxE+Iy2aNmvgCd3+RrKf\nTHuUZ1bCo4fIfjOPa/N5tZt1XW9BXktwzXfok4yjhkA8t48/T38zzd8KnXTVO/PAOIZ4YGNuoRb+\nnQXrnlXUj7Ol4nDN30fd4ss1ls8avVcj43ljgQTA0i8AtdDjer3lMxY6uo45PYHcr0lPPY+1FcMk\nBvbZdJSJdkVEj6JEzfMMXGr/ao2Ui7rzXDhLxmMvqn7RPQLBpJsDj7V1PnjUEmu+88PTYVzH/Okd\n0pppLae64p0Kf3KMs+bfjGnsRlNsArLVn2id/ntVxVIV4fvipf+zav7fkG1ZHfZJfQdmd3AdXW3D\nPHnef8HqIIL6/oNN3Bo4JLzGYWtHr06ulmoLBhX530zDRNp8efnjwLxgxzeHNNgBot/FGKsKSq2g\nKNWXdjQfEnrrU2CDcehJ81e/iS/SCvNPftDwoi5F3Ldmbw4JnB5Aelbum+vNvNH8d4RC5YR8GtSV\n3cm5l95hnlwZsBgLmvckBWc6EY6M5VcOcDskZOxUsas6JOJ209cWBDaf+ZhJKOlYGrmh/isLxgML\nQZrTNBLs4+9PM6nyc9VBvtX8tQ8+joxQUY4346PPfF9t+2c0bb5P44Q1S45SnrT0T37+bsAfDUfD\nPyPyJktA2xdkYJg4d3+pJ1yuqx2+sMOpPjy9f5uPnnt7KYX/aZEJzqT5q8N3R2j3w2wbQrUy5ZO/\n7/2vbe7POcZ3hX+j+TvnfYvdTuNEsI/4GygXSEmf0Es/vR4u4At92Auikn/z4kp7AoUgMTd7faxj\n7xHEdoDSqql8J71nGC0RueW7oSPmSwPRrIFtGUtwuonwbbXqvYCdXfrgDrxQxtxq1X7H6XC2OZA7\nso5UI9affujUfom2X+68rq0YrfRUzc+OoKzjAWD35CAoAOgaYTx0TaQ4tlYMUGihrcICAIfJlRET\n2mRZ7gkvx8q1jnXEnv+l/M6CuGU48Xy6Fm7P2cA+MlcykEoRYIuH1n8Ozfrngzn4da1jvVxbH05a\n5lUPz86i+us1UGn+O/j+3oH6vNtLKfyXRU9ZpXF6fhA1rTzx1IJuHK22aGuSv/76hzb3r4LGdhYC\nB7iUe9ZaD//NdDgaA0k1M3U2l/6RFj7u51kZmYfdPptgkSosnSCqreZIgmk82AbQMfd0AFUlA4cB\nHFzm5qxHMXL2xTLmrpoPv6+OHzY3lXOZruXAsfLsutC4jZk2oEEqzXwAwOFwvtH8Y8fCX+pF6DTJ\nn3LK43LPOrdPfUj4dWPaHt5PO0S43zVzqXzWav5aScow/8RriJSgcTCYYyWheX68t7le75AbR662\nRH0umUz3D0Ydg97bndxbCyjtQLYx1p/ZT1mjK6f/oP7tW1iinJEsViuX90kd5OUtrl5pTusX9BK1\neyfVk6K6uf1BiPD9hmzh8KXyS9YydqQptJGdWNFPlPM81OyFB8fXN/dnbnRtitewj9fmbcL56b0e\nDwenb0rfzijMmwurjJ1bKABp/nxY7DzDtA0aQ02vax2Lfl0/jrbBbPHvWB9AKQjOrCkO+2/z23CE\nKM/NKiPQA7EW/jzXjFvXWj7XaN3N7cOfmYXhYzoeDhvhzykOBtH415u65gNbHOVzvXfr8K3X5FTl\nPtK+YvNZzS/XnySU5DPG9AEgDgNCduIAWzEdHd4lVcUWjpir8ox7QnMrqMxRminlRuMc9fHtrUUR\nxLxvCILRZpp/M8eVli/Xd3knHmbHAunob5V2zX3jv0mN1j5RNHtExiBWk8f+bA+ib8I+z7GNH/1V\nAOUET7EWLl2j+UdkDOOEGH2zV4cFaWXaqnwqlfOn1mrvyuXCEZhnxzPDfPVAOc5E+WJ4YD5YVS3A\nF/o8TfRZvcj4ur0ycZp7pTxLx+Fj6g8HE7S6+GvNn62E/cIyPI421QFnsgTcqWzCn6CS8G6wwR4s\nsiPoW252GZP/7TRNSNEPMQDoKZZCNf9otaJVqO+PeS+wp2J8Ddv0FzU+vh0z4+Se9TLIWOptHdMA\njuTmoEC23OZ5v17vPB+R8qkaa5vfpm2JBHVGrO5XPqex7K3FRpgDrnRUn+l+bizKuOM81Yyb5f5q\nGW6d0MyC6Smws009wffRv+872otYLSMuBwa299iLPN6b0+fdXkrh7+ZZkKhYn0gLoLJNtmIYD165\n6Q4HDLc6Ypg3QZuL3vtTRzf6vYbDhfkh9J5nO7VQgVJ8I5Jz0GCffquZ7QUEpR3MsxaO8kwOEpoP\nFW0OKNZU+zygaI4Vo2UnhW/73MJG4vkuz7in5RpN8+8qJ29g9s2ONmoClw5nTwWwI1jpfsNQH2Jl\nzA6tKdbvycv2x9z2qxoz9eHsbJv+osaVpf87OWdqa6i0LrGNBwRJL+CR4v7+OhHqADAfDg770EE2\nDp6eoOX5t33V33q4oNbsrXWcwlYz33NyV+PboVp2oVbmPB8RM6h0/e8F020FOR+eKhc4GK6yOivh\nHzCMLPwzovhbbP3bIVDHWrS/fxPz/zrab/7ar3rEYlgRQz25fadZIXVyS5Rm39Ve+qe1ygTc0/yb\n0/vUYsGtcDV/Q+n38bAtAQgA5/OhSrKlC32etlkD9zZnH7rNdZVjUdkUfDjNB9PiFmMdbfsAAIfD\ncRd3L89r2Q56Xc3iWUUwve+jH5W+8CFBm57usasZ78A+sOtqbQ3wms2A+Ik0utqov6z5i/AXpdkK\nyzTOT4v2bTH/0FWH+vk9x9TfLTLZ743tZ5qOPDbCP3YVPMRrqCNY8XC8QOUM1nVMAWu7zKMdQdUT\nXGKa/47FxX+/dyhXNQD2ePZNmmXTrHf8Gl3YWs015VT3Cfl3OvUNcTAdxblUUFwwdo/2M9LhwT85\nxcautfh0EfRc2ksn/E/jDdE6lyoiEwCSBGH4Syv56tvIvLb9E6855bNy+O45URs8cSMI2WztByRZ\nlKqZzcM2ohIAhrFH2hG8w7yTNXNH8+938rLX/So/O9rL3XQ0zV9hKRaULFwPxzPzSWwKdpsAlOeS\nwKy0p74846MfPK/62VpkFeOoOXT5OVVA054Qlc8GdrqyqS93YDqtwj7HK6UUl9YyX1zz32pz/Pvx\nPq+tuv98baqCvOQZO1BKG5gYJMWHwkM9FQ1h4XU8HPadohShuqtcYNt60Xg1d9TaYv57z9lxAlef\nxR3Yp2Hv6RrodmCfvUpZe47ngZz7WoiI10JlgTZjmoa6dkVoI5af4mvgPoCe8aLaMwV5fSO2h/m7\n8fm/+yPA9wCnx8VZWzklhVancMCKUJKXWdGXFoYAfvcf+ThyAylYgQm6zk3i1uEb0d/l7OKSgUiI\nebE8/vosbdM4WW728p1skK5DyieL+i3PpmeoI4sPjl0tWBemb83xeCTO9DYIzce64nh+DvY17lPi\nai1vbXDysb8HXAPnhw9V9zihr2GkKsd8detqLJVmt8cgkV/HuyK5VVumeb/84hnwfuB7huvqvi28\n10Jw/E740Dzeuw/gC1Xfaqqn3o/+nhyq9jz5jJ2O8k0NlbDwXzUQbcE4T3bwlb/aKhC7B9mOoBrG\nM7mvCv82mR31bmd+9mpt96i1aIB9ePW8MUznwn8LV+5BTRwxn+S9h5yxKGSMLeSon3ep3ruhgaWc\njbSv+btz+sUL/5dO8z/7QMRrj74VAPCtFyXDdMtlBmCVm9TBWAm0Hc0/NC9rD/bxSEI17UorcMA+\n7IMQqO5nQsJimjbfq/Sxr4SQaYTdCE+fIJ/RPXSB1tkZ63uU6+SZJDIHw94d85zTttxcxIJ5OjaR\nsDvm7M5zWRD+o+//KADgffMrVT9brboS/osyPrZjrh3y235pmw+HzWfM6uL1kd8uz/u+h3Uft2yf\nFiffzgcAHI9Px/z1bVSY+Q7zRRN+z3Mt/EMDO46Tj6WzIvMLxmHEXpK5cu86WjnszDX39vz+fbvO\ngrwafNyarokdjbqCfUz40jpQWKWBcSrhb9Ydf1b/LPcoPzmqf7T0DPRMhn3YYRwCUu/wZNH8a9bS\nHty0mxjvPcjt89Jp/p///d9En8tmev1BSZHKi0oLi3Sm+cvm3ilYcVeLOVNWQRZirWlHtLkdjVBb\nJdApGKztyzB0lclugiJ5LYE2t4/eEwDmioZW36P8LjRLEuA95SY5SbDZOJLwl4MsYcU4DFVhmRpe\naah4d0zxv/JtH8AnX3uAbz+MVT83DmQ24RfN1/R02GeP7aMC9Xg8R9sCVuRQxjoOvj4WYXR85/tf\nr561wfwbLHvPGgNK+b6YF6lgVf8t95vTE+g07/Hgj2cPIMiUXFuXUByIXaTCP2JFl9JuHAlAVMVd\n56z/rvvig9/y4fKdMHjW3Ka+2DJvaj/H9t5KNKjWQdc6fAX2GTto903zJ6G+BwFqjw50ePayZ/i6\nijhRFQEKBrHl9t5EMNnc4ynQ8YtsL53m/63f/vfj/g+UqNxXv/9jAFAtfDWJO9H8lVo27tSZvatx\nhOie46bNLNiyO1rBx87E1Bw8jBunLqGfp0qzAICY0oZHvAcbHA9OId0LbjLnJ7FB0DjUAGCaGPZx\nzT/FVFtIO0LWnsdaJadWSBF/5Hwbt9CygioISzd53hEoPhL7fU8DPd9J4xErpcHn7l/42c/gD/0/\nv4F/8EOvVfc9NU7NrTKwPRiA4og0oZCKH6GaHxWEK49v63NSwX1x4Q5kHwtp/mzl2uG9iGOX1zP9\nfcPWugv2+U58DgDwba+/Wv0dpz8HULHWmOrpnzXrBbB8WxV7TzT8tl97StLITJxdy7f8fnbmRVW0\ntGL1TFbO2HJAlIO2FvT8u6EDO7miSivfd+8B5v/SCX8AOH5v0ToO9+vQagBGxeKC3UC9MN7N5Kow\n/x3zt83t0zqR21O9zuJZP9sECBaElND103ZxJc5cqJuZ+1s+Oz/j+AFI//Pmsz5t8W/uF7OLksEG\nIrwqKmreXNfOzd6YuXnxmho663uy1NZ63svf6SbbHkZ7QubevT3hT2OmQLof+al/DX/9N38NF/ek\nMptp/o1TusF5q3uz8KQguBSv5W+3hzfnVLIU06ydR4Vc3rd5Ho95PriVYzELCuvw+8s7wmvXYem/\n/1v3/jZ+Mv/reP2ihsTaMe/TLrm/8pMzbO4I/6GrM+Walj9zhkwR/hUxYs93UdrZuZdTnM7Pt32n\nOarYPlYjuRb0fJ3JiB3aNfencu6/oPbSwT4AcFIHp6VjJZN3qjV/bf1QR+Y9rQWCfRIB9CYATQCX\n73KoYw1i8+yuHxHyghy2TCNLGYGSFTTNM+I7axV+H6iK2O5Gks8uzh4Cj1F9v4f5j/1+YJu2icoy\nHk5FWFmMQ9w3Z/t8N2b8tGjGuwJqqgIjMmV7tNuO9Fd17u6xTu5dvA/A71fPrsZ89PVx/MQncPzE\nJzb9b5lLxu22VNlbYVrdIwAp3KJt+8J/G2GuQunhxX0Av1vdw4X3gp4Ttd1qUJ28nztSPzhNVvrE\nsCIJwD/xR/8DfN+j/x0pSVqDXae/x9vwNXvWKh+Chr/zmFNN3dY+D93Wkp/nI5TZ6v4fHocoAg9f\nBd6WZ2oBpirwkyKkV4+TsGjgHeHPldfKz/0Mno4e7HGonm97KTX/20b4O0654CgmcdecrAcuMv6u\nsA/QVhIqzxFBrVWMOAc8sxaaZ3fjtv5v+3chZyD2GId5q1mQ5m/OwR1M9XCgAtExVNcDMMhmHPbT\nWJd+rOhorqb4FoBSzB6A0Vatz9oftRDWrcb1NHxzD8oBmmR2O3+um62POxpWdfCU7w+7mD89b946\nhO358ogW2uismtWettysgUWE+aosHrpW/n6KPuZuh2qs2vT9yS08v4evr5kSB968KZqtSEVO/VCz\n3tSpfreWDgBdd44H9//Y7j1q2Icpy9vv9+Id+lHz5KgWvaAfhup6T3myDXyczwn23FF+tB/Hi4f+\nTBP+1A+O9ibh35vmr325m/nVV9HGbLGWlr7RhX8I4WEI4RdDCJ+TnxvbOYTw0RDCr0oRl18PIfz5\nZ3nmV9PeOpWFfNbVeHVENk58V8tYC8Mu17077ON5brYvUTW+7g5cb5N1cZhJQDTCn6mRMaIfz9Am\nSUNVQlIXHt1DhT9FDsdVD0ZeoCIIp62gY4cVC8L+tmj+NxAWVeU4p83eZOm8y/nZtoq1VAljotQp\n+rUjaPqO34H+XDefMT8bzXUxL1V+m7bV0Aa/5+bA43s3Yw6ikT7+/Q9uvtcD6kgVtdTnUWv+5bNz\nsWI/nH/L70FQ4UDpQHBThJfVHkhbiiQ/Zy8g6+mH9/7vXBs7PsURXznGZVy8FpNApu09WDkwR+65\nC/X9qPBy5dmZ+0zGs4vNGLm0ayX824AuHk/TPy4OVIt5HduLb8/6jJ8A8Nmc83cB+Kz8u22fB/An\ncs4fB/ADAH4ihPDBZ3zune3vXd3gJz/3/wEALpQJQFpPN5dF0TfrdeYc+u+C+YfM+XC2At5w7Tu0\nqK55dtf1uFvzr+/ZT36taTsUyLaH+eviGsipHXd44nqO3b9wC2EzNqxIVJB9+Vy59haSdnonrL7u\n1x7t8SnCY+dwBZq01/r5TtWu48AZT+u+lGcLNz5sEdBAGhwnX9tedwdzQ4S+HgJhp382BslE+4HL\nV7bfK2zHFM1e2VAkYDpN7Zzw7+R/CT+Fv0Tj9Pc3kvAf5PC+vi7rv7/j8LYRqr7hgcFPPbz3YDDA\n+fPlmuYZ9Bw/BFYMgsVX+1kOba5MB+xXH1P6Kfernufyg53F/bTV/DkOoF98TJpdt4025v6ptKhY\nVXuaf7WDX0x7VuH/SQCfkd8/A+BH2wtyzjc552v55/gcnvnU9qHRN/vYRAQGZPRCUxyb6lXjtGUH\n3NV4U3R7mr9s8iHdpfnX9+unwy5DACCNTDWabt5dXLpyDSvdcXR2FQNiD15Qh6FrSH69PzORc/x9\nsvj1MOzvCFCzxb+jBT9V88d2HAAwj8xV38Iq+lfnFG6vb3xvzGPabja2sPpu6wT3e9DvOz4U43jf\ncR0A3Kbyni/C2aaP+vtDSq08N3AHUDvqP4LfwlnaOt8jVsyzv78zKXmqlOc6Jw4J69Zh+dVq/ju4\nd3nOTg2DnUOZ07DM4mvivFydzsNa92vstw7f6YI1f+2fN1sfoUPIC17Ln0fYoXqOdLB0J8q6m2rh\nvx/tLXsxbWGv8rtSQe9eb8+rPavD97Wc8+cBIOf8+RDC+/cuCiF8C4BfAPCdAP5izvl3nvG5d7YY\nAv7WP/AxvG/Y8vYjVvSSPmBs8p8Mw77Gs9eqE53ZEaHW0tkxVEcq1obeMPaIjy6rv9WWgpjlqpUM\nd/sHALjzM2+FZiQBlnYonGoNXDx4DR/+yv+Nj+I3AXxcnuUbLpJJ/epIKiD2o4gBN8vbBG+lr08R\nHiRZGdaZz86A4m7AYFRP+ju59j4xWwLqVABlPGXM7Buo7hHKhkzxbk0s3HFAKVyzxyzZxnpIYsF8\ns+2j/PrggQuvw6D4Nwt/n/s33vgvMfR+vY4lYsVATKmLrnYwpyqCnD5vErp91Q77ag2QAvQuFtlW\ngAaMZ3Pz3Yqhrx3Lhvn3W/gqcobevQNHxxY6/Az+bFnr8X/b9I0D/oYbh300/sX9b6T8NIdTl/ZZ\nVfbZDvT6vNu7Cv8Qwi8B2Ca1B9mU79Jyzn8PwB8RuOe/DiH8FznnL+w868cB/DgAfOQjH/lqb79p\nH7+oJ44XS9dpwZQaw+2qIujvgvlXrAXaIrI+OtGG+7RvTXSN8O+6/m7NX4X/qteSc3dvs+hGqgLF\nZKHzgtutRFba2f334d/FJ+Vff6F6VslU6OP6/mNNK9yrJ1z1a8eR9zRLq6pfwMJ/OkKjeAYZaqyy\nXpbf7x3uUx6cLdSVsBX6bf/juwj/vbkGQI7luyOQtY3jBJwyPvjtb8tf8PyUdnzffSMkTTuOyESH\n+72LP9qMxa2YSI6UB7JVTlGzlz5d8w9NJtNy3VMO7zsOvHHmgkXYjMXmnmo0HHY0fwtCbEgUQ2RC\nwM763ztwlD4bAiZI6o6wVZIYAownj6abhjomoIYAa0WAlSRmINwK/Pjwu18YMu59ercLcs4/lHP+\nwzv//RyAL4QQPgAA8vP33uVevwPg1wH8qTu+/3TO+Y2c8xuvvvrq1z6aOxprBYohnx9rRkSNwX31\nmj+/xBxqU5WxwcpZ2UBOUaqN7T3bw+rled1+lSrnRct1ezxqTk62V5JO7jIcn84WiaT5fEejobBf\nobq3Co2wp/lvHmdtLwc7AJxRwNpolF5vev/zczdG2wIxZTz+V38u/4f4V7v/2O9BY2bfQ9vuFOqi\n+Zvu+pQo7yzC9/ixT2z6qO/07BXX5OdZEt/dAfu0LZA2GsjK+UMfKoGQN3JwDAyX0N+3KYn3Dtrd\n51ZrwD8/UDoNpbfW1oSkRWCGl9XDJWWur2GfLL3uduoiV/2y5/hnT1MEKuFP6z+dWPNvcvfvOXzF\nWcKpJnj+fhC/DAD4/g++cmdfnld7Vvz95wF8Sn7/FICfay8IIXw4hDDL7w8A/EkA/8czPvdransw\nySsPGlw7RrSRs3fe744Nl5tfKgcrL+IGX+77ux2+zmEvf99TZbLqWjPH5QCKW6EZCK5Rs7ha/OKj\n6Lot1bOyTOhQO37v9+Jf/Ov/Of6jq0cAmqyGO1qfolFfLdvnriRax4kCcaTfewLp7MyViKEpEQig\nSmT2b//DfwV/4U/+ZXr2VoPb7ePOQVt+11/0xz48BHhAr1qSe1W7+nMn0x2OnjhN2zBu4zPsefT+\n+CD76Cf+JABgleeOHWvMWwvYmUv7QUptu+tgPHC0edizZEtjVt446Zolh29fO3xVAevDvnC1z9bt\nXn8aubLKwkrFlo7kmFVrbNcvstL+QcnTtffcn/rYx/Cf5D+D73z1e57Sm+fTnhXz/2kAPxtC+OcA\n/BaAPw0AIYQ3APz5nPOPAfj7APzlEDSMBf9+zvnXnvG5X1PbM8Pe//rrdUxPjELhjBsBvG0k/Gmz\nqNahX09jXdVH29TX0973d8M+V19+P3AAwkkcqp2nitirgKUaxh5fm81eDZLi5ykmHsKe85PmkATm\n8Qf+OP7id38MSZgUff//t/ftwXZV532/7+zXeZ977lNXbwTiIYEQQuJhg8zbGGqDgRDTjE3cgF9x\np7R1WzrMJGTcmeLEbjqu7aRAXdtJGjvQ2HGmSW0guG6oDSgGjGIMCAwGS5YRQkJXr3vvOat/7LX2\n/vY5e6+1ju773v2buXP22Wfd9dhr7W9963sGUVyZpLVDeN2OuHROJLOph5vhdBQwj1tl0ZOWHalS\nrwK7w43Ji0Rdcf2JQHSFpEVP1px0IiH2YWPpJCvJ9H8dYp9CUvdAKVnXvFIDwOvhuGoq5DU7hXrZ\nFklc7MMxLC2IiioXQOBDSjwSnGHkaCZUIhtet4bzz5jnZr0GHAy/j+8bDW+mnMh8nvvCU6aUqu42\nXMVtR5x/CJ6nWMv5JzKSZSOR45mdjPsmYguicnMg6ldnu/F7GT4/Pld8zaxa+etYsfzGhB/ETGFK\nLQgh3gRwecr9HQBuk9cPAdg0lXamCi4jVBgYHAD2vRkX4jE5DGKfRJpDpvkX0UuunKXSJ7jUYVPu\nF5kSt1Ps0+qIWkjxOFJDwbaUsjleyp2EBgB8lf2LEySlBE4RcfBn2Pm7w0zogmIQeRHz56Ry8yql\neNLypas51icmp2UvKj9x1ZT1SgrBdJljj0qUnjC71bzyaZ6nqeUyiL8iGGpd6OTkymqs5ihxHN+U\n5bNjMv2itPzh7XFmI3ssyY1sTcnHTSNNXDEQnqTKfhAR/zQnL0+JaBJjyWw21XYfAAYadeC1UGPv\npAZJDK/5WUat6QTn73td/wskRatpzEUkhknoGTRin0hX1YLL9BXL2WmrVmsk6kxszOrkTiFnVPTT\nreIAzArhBxZpeIdOcHtthUZjAEBM/LMCMqXXx7h49sKJDtlzMShFkQUTxL+YVDZ7XszNdyaEVmah\nvoy77hbik0lq4LSIw0j3tFUIyt3u91zv0Ym0Z5gGPyH2icuW2iHRqIgjYbspdafBTclZDCTHV5OZ\nz5wUwlvgERpdJSJgikzXPGbTekjmFujuQxpT0UmshnwXrx4bx5Cf5jnejWpdhdpmp6EUR7WoXxlj\nKRDhCxvWRN/9oAgc6h5LFHBMEv+kOCf7+WSJ98qVPihzrUkomX+3FitIocdppp4qZErEBGXkJVBw\nI09z1qJG7sOfX8BEjmv6Y1FcqdhItMfHq4wSHCnzD7wi5LCNzOZMYYkQ/26uui6JQrV1KLoXvxgG\nTo9dc2ejiMNrhyVK1UoUI4QTuD6WsxUAyHHDvhEiBa/CwGTYz4q0Jy4kNilGTCZcwAHEuEo7mB5g\nTaGi4vTzo6nOoiVDbNCJUlBEmpfiTW+/gPrgS3jHkVfC3xLEI7tOJyNfMD991ErKBDBGFOmT+E26\nYQAAIABJREFUiboqReUhGpfTcv4ak9pEuYSxQHz/4reewqGh49h+6HHZbvoJAQA+c9oqfPn1N7C1\n0U3U03qoIqsmRWHZXsidDohZKJUCAJNddau4Qo1CN2HTzV9iw+Pyez8+kRVFMilO2Lb0Nk8RQXKF\nrxIFdVoMZYepSPYraYWnYQSEarsNl8W2GupbgW0/O4iAjsK94PREnbzuhistgVQU4WIpIv46sedM\nYkkQ/7QjLxHhvc/8PfoOvglccbH83U7swznaKhMrqGxfbfnyBMVSTPxZldV6A1cf/muchWcAPAgq\nUCbnP+6pxSztvwsUvsDUoSAbD4AiMDkW9sfP8DFQqFSbXf3ix82NPxyD324Dl6n+q5fewPkHZSi5\nD1/8x702bsBf4g2xUdaTrfxM1JeSfalrLGUVvRXaskr5mzXmTqQ703XDSViWxM9H4BA+hi/gl631\nsk+c+Cfr2Fgt4XOnx+bNaZYvHCq/QO+cv2HzLhYBjHXV7U+G7e0/OijrsVP4Zjm2cbPUeuSwxp6P\nvBzwUhwOGefvZGXyKuhl/m4UboTVq+H8E2a/PAik7+PqJ1oAfLi/GURl+P8AgFMJ114rCiFfjk5Y\nc8X5L8rAbp3IOvKK9nI0TruMlbPj9Phir1XjI2BLLvWI+DPFUMLGuVLFB/EVbMZT4Q3HyST+b0sB\nrENHu8aTMD+bDK9XHe9OTkPt7sXVGO7v6hdXri4TDvpHz4n7b0k8eHjqRDiD5ddg/4t1PH3s5q6+\n6xa/65mJfzWyedcTpMagSr7Cxuyaib+JW/YSp5P4fnkkFKe0VUwZTtwMIXsTlktaM1PVxxZcTQiK\ngqUlW5nFMOLPaXtpAP0H9+FtoZz+eN3Z9XFRXJruCQCqpW65vSL+g41u4p9g5pR5tTrpRZx/SppP\nBjeF8+dhpjtBrM0CCwVDnoezf/xFrHn1f0en0TSP5fJQqNR+de9aAEDRt48oMFNYYpx/8iHf/69u\nSHyPrWgMLyb7vdaIPUiPHKsBJaBwPHysoUgo5KI4Ufer1YRHBDEz005CowhokcXQTeMsvIlww1kl\nvSC9DGsChb665PwTPgvsiH1X0gmbL34d/GK6k9e7zn8nznvkP+B/3H6+7FM2F8zBs4ZlzUutqiJT\nsv6mlGvKzFsJ88gUsULcL0vTXy9dL9EevhY4/iD2Fq+V/dNzoxyJeP5sNA9uPhmHWTwZztjwsORd\nfbTUX3heABJtCCok5u/6Detx/3/5e1zxAUX87U5uNorhgaoyPohLK0JcWz4C7O+sM17/1OFbo0SO\nTsGJx5Gm8I28r9k9rrgvBGi3YwcuLvZxWBBIt68PA/t/goH9PwHw+7J/3fRm4/IR4PnXsPqkrQCA\noFKEkvvkMv8ZhJpSE9dqy93y3/tYghTnjSrQBOrtcDH75RpUYm7OyRUHBoGXeYXxq9TJ+bf6Xwaw\nGoXS4a7xJB2lQp3AYF94vEwkO0kZz6BM+EEZR/FO2D4bHu6W92+4XsQr91wb32BUQUc8PN9nMdjT\ny5VlFEYnw+rmL364B/tqb2Noyxldv/F4R52wFZX4brp8efNJm3Ht5/8z7vvQeWH/YLfhdfaRh/e9\nqJkMPZ2URZvHYhLbkRMaHwgk5+/MFQ08/TtXoq+sTIQtiT8nrhnF1q0f7SpLMmVlbe2pwP5difKK\ny0+aKatPOWcUm26nbbRqpSdFTfE8XnzRk0ga67LNk60zZ6DbGSuNOXv/sn4UCoTrhkOmy/NKUHKf\nXOwzg0gL35qGmPs2cf7xouO5Xbfu3o33Pvka3r0sXERJb9f4/0uBzAA1KX9nFjydR+NmUdr3J+LS\nd1v73PK/HgQAbNy0UrbNohqmiBiirEOsDl3wMttTkZOIqZJNaDjXoXve3JQ2K7uRcixLRlGNf193\nsIrzXl8OUpY9nCB5FmM2ccvc45ONZcPyOp779DW4YsOIrIeLfbRVRs5U4T9aiH3Qhqsbi+gmSKn1\nFZgTYce8KMIPdGxkuvp4HzJMKesjJ3X1TSUFSg24lyqy6R67Tofnpaxnrrtx3Qpcl8f/T2cEvNFR\n1K+9Fmv+5Gtd7SbEiwXCjcv64cpxuX6xq/xsY0kQf64g0sHWo5O/mDxy58c/dgMubbyEK957C4BO\nWTCT/3llrPjRHVj7g0+H7RFFxEolPVHYtv79AIBT1rwjbj/Fzv/qWgGPfvwWjKwLuahiwscgru+D\nu/4rLnnsd+MbnPg7Gs5Rk5KQI5HMRVOUDDJZhSKLQNl5KlKoqNDdGZx/1I7bveH5KVnLOuswEcyi\nRjRV9FjKPzbmzlzNneBcslYWzTYo7jXaCVuxDzwfaeEJutplyeR1+otEcLiMcn5Riu14jmI55mJK\nwL3O8M0AIKJAhd0isXTOP+mTA+hNneM2O8SyrosVn/ssytu2sbJmOuJm+ADNJpaE2CfNySsNtsd8\nzt15bMEMjK7FP/3oHXG7KX0AQmJf3bcZKHFzzHTOf6BUBvAmNjBHqrTgaMvuvhvjH/5NODIWf6US\nR73kC/Yzt30RrXa8wSTit2i5YPVpeDYZ8eC769MTaoVEvuBWBvGXG3DS6iauv3zuCI78w16QLwkE\nq0bnFWur8K0Ui0DovqBXXvM0jIb3nW90pCH+fG07KVxyVM5yLIWCZ8UEJcKH6Opj11mxc5ped7+V\nCK+YQpDV/PHeuUF3ft80T/imeBNv0QBKSubP+uRq9D9ZnH8abMyinYQhgymiwMxgSRD/1GQRaeWs\nFb7xZLk6xxCiWOnUMb9DH9sEt59bVnTXDQA3jfQjKBRwzWAcyz06HbBueiPD8EbiIGYBT07DXfGp\nkMzTyt3nNaaCBUuRGFEBBdFCmxwtR5+Qz2vqC234Q8VbFufvSwKRCJPLxtW8cT2a15+cohxMcmCd\nsDX1rJTKEfHXxrlhhCzL8iUqyxOXa61Qkn3NLqfGokfo7Gie66w8C131ZVxzDEdeumxNyLlsSiK5\nnOXpiHw4uAWdFLGKVopfAFs3d03ejT3uKPzCqbJP8bPl1m5Z4zCHfmHt6fwfmIhVt2ZmEkuC+DtR\n8nCT2MfOESbK0Sta2miPqs4WCokjLQAEaxuJ72k5S4FQ1n/DSDI7po3ytVysAVA5AuxeTs+KEJoW\nfwEOWmjD0bbLRTRaO38vQEz8k+UuxmH8X7CMXoyD5PNCBQIK6X4PjqcLiWAnJ69WqsCbZlEJ58yz\nlJ9pfSxYcP4mom7rsBaW6eaYO2EypYzrYmKVjl7+x1NX4gcHxlBSYRvYzyoqZ9kp4Esb1mBTjTFK\n7WjHi+CvXw/sB/a3ui2e+NMbEvswit1oextln2I4OuKfomTOQpSASXfyzcjkNZtYEsTftTTZsz3a\nFSzl3wDgYgItuCi09K9nlp1/GtRmpiM0Rb8CO+If/8ZtjzthK/8OU0qa+5eUz2fXF4bPkFYRrWTB\nL73zPIxNcuV7d4KQ1D7yE5M2PaP61M9Jo1KDkrHp2s2yhEpDwntb43mt4y450hKWZ5a10A8kQqBr\n6tIR/w+vGMSHVwyy33n98bcu5iclp4CQClRRSUmCkjLmkozPw3UXPK9wJ2Lmp5VZRiEtYZEOJhHg\nTGFJKHwjYmkp8zdNWlpQqCx40uGLDMRfvewJK4+s9i0WV8AUpbbu964mPICtSAzgJygNF1wwO28B\nLAAdAK9jYxzyPZxUjol3IsmGrn9c4evqErOnn8Y6UUxYVmWX85lZaWcqz0643P9C54VsoVwE7PVe\nIWSdmqJeQsSWXY7HYNIprsM+so3C0Yw5pb1Pnnw2TvXewv3nviulXvZs5EtTqch8wKxPns7hrweZ\nf2yQYcfR505eM4iYoNpx30aLlh6OaY6Kk9LSL3y1uEyyYCBd4dtVhsv1Le2weXalzDanSWzAs0np\nXqjA4KzGUWQbQZZZIZCUp3sljdjHUtSVSBauKVpkAf10/ev8vaBT5FovRbuNDODKYY3yOiPUdldd\njLjqdBdAkvN3NcQ/5pTjdhu+j+9fdGlq+cQJQcbdqsiAbHxD0vp8KJ2cjdhHJPNum5Db+c8gVAS/\nFjTHZ7Bjfg/KOBNiLtjUtrCuO86qpGnXSbd572qXc8FFG87f2D2kxTPvhJ8REqETnBszbYzVeuwA\npVvYiexXOmsfS27PZ6krdWKYYqU7mXwWXCYW8zREKaZFdpy/DZdpM9fJtKfZK5GLh3SmlEAyvann\nafhSOWbHQgQDJGXq/V/xcfTZYaxdE8ZbcpiFj6c9Ycm6rJgfOzFz3L+c+M8YFOffNgw3dgYz1NcD\n5x8vhGx5Yvi7Iv4WddqIIyzTUiZEIFprn144fzlmzUbm+zxjVDbxCAo87rl+YuoszpKOIPF+aWX+\nlnJyP5G3OLtdvjmZjtwOM6XUpWe0lRfHa6aH+dNtyoGdfoU7DnIRUBr4hufqvM2l7seW+PNlc86a\n3XjH46/CH1kRtsNOGLoNx9ZXCIjpgy1Rn6uonlMi/kTUT0QPEdGL8rOpKVsnol8Q0Rem0uaJwLUV\n+1hOsJL52yw+VcbVOFCFbSqZvwVnprgQnTiHRzXUdDMR28fPFoHYmhTyMjri4bMcrqQp6DIi6Bre\nuzrLcWuTmB0wKXztuGWfc7eacrUGM9c1vHqc4Gs9d1VicKMxA6zK8TJaXQzz9tXas7MTgk6mDiRF\nML4mMY3NOxKi27TXu/530X/qYUDG3ufmwYGmTVvdCnAiYh+rYtOOqXL+dwJ4RAixHsAj8nsWPg3g\n/0yxvRNCxPlrOEzAbtEDXD5vJv7HjoemiMVsGiPblNxCD8RfyzEkrDE0XDC79jXWPrbKz7A9xflk\nlymxPKg6s0fePxO3XGHhtUmztDnn7wdT5/aY+kJL1MuM+OvMN4EksxD4lcxyutNVotwJzJ+OzgVl\npufQrC9+KtIproEk5x9oRF1eK3zvTCf5SHHNx3zhbwN3HwRkv3x2wqiUzcxPL3b+tmIfsqAjM4Gp\nEv/rAHxVXn8VwPVphYjoXAAjAL47xfZOCIr4CyPnrz71k+ZayoIBoC15wfqAYUOJTD1tiL/Fi8xt\nyjXKZs5FORrOrBexjw3nX61w+bxmc+KiAINPRcCSbOgS0xDzuXB1IREsTli99LHcx04mGm9SAPBZ\nhE6dIj5yeNLWxpXXPawvzcbCN1odEeG+I4HmWQOAx5TIXilb/+S1QiMKM/GX/dOdQJnOp1TWPGdV\nl5Wdv52/UFR+gXL+I0KIPQAgP4c7C1Dom/45AP/GVBkRfYSIdhDRjjfeeGOKXYvhWhL/+AXRQ70U\ndvLv8CUfHe6O/pcsp8I79KBP0Il9OBHSyfzZtauxKulNbCDr1pitcuLhmB64hJ50AC4z29TZxqtM\nawDg+2aX/l5M8RwNdxuUY52ELpQAABSDeCMLSvXMcjpzzES5iHO15/x101Jn6Qt1p5iAidV8g+jT\nY8+kVMw+7XgtOwMOBR0zVy7G3H6xpNN5yU8bUW/bfPJN9G9ufLzMpp5E9DCAZSk/3WXZxicA/I0Q\n4jWTN6wQ4l4A9wLA1q1bp20/dCbCdoWhfdujcaEHsU9Q8gABrF92tr6gbFKZhur7KT91iyZhh63h\nrNlQCzoPxxPg/HWLv9HfBPYdkOXsqL+rc3YC4Hox56YrmwhKptvwejCPVChpFJU+I2g6JS4AlJjy\nuliuZpazNfW0MhKQsBl3o38A2KdCEmfXVSxXVVZIBMVssQqAKCUjAASVbM7fl8yXNeev+Y2fFoNy\nLbNcL+u/F8uqsG6rYtMOI/EXQlyR9RsR7SWiUSHEHiIaRSJFSYQLAVxMRJ8AUAXgE9GYEEKnH5hW\nFMz0FAAX++jLeT1w/qWgCBwbR8nVE67W8QpQAjCWvQAjRBuFTpOb7VnJkYjRotkce+L8hQBILzYo\n1xsAQuJvcv5RCDQROAHAYZylo7OQYct+usasUK1kc4+c4PuunhBW6gNRHoNKtZFZLmYA7BgWUzx/\nwM7ap1xpIPK81phwlqplNc3aHMMAEHiWnL/sl2vBKAH6TaxSqipHeBQrmhNWFAjO4uQUcf6LW+H7\nbQC3yutbAfxVZwEhxG8IIVYLIdYC+BSAr80m4QcAmgiHaclgGifNlxl+bEy03jccRuNcqUm0AQDj\nkyHX6h7LljsqKDNGR2PGw4map+mmTt6eKNeDwgsWnH/AHKNMIhCFoiZTFZC0cNLlJvCsZcX2m7xC\ntU+jnOUKTY1zGQDU+mMxYamsydBla/kSzZ8ZNifgoMgV9tk8ZIWfYAL92uZhyMsaPceKY2O4RDyM\nj+KL2voUdCu8xMWPQfbcObYhscEiANiKfRYo8b8HwJVE9CKAK+V3ENFWIrp/qp2bLtCkHYGztuue\nPC6vzLP2L9eM4JvnnIK1GnkiALQlYfBsXmb1IpMd5+Npdj3dqYCjF2sHVaOjadfncW4M4hwFnUKu\nEzrHKF3qRo5e4uEoVGoWJzcA5WK2KAcAGiyEd6msM0dVcexNnL8sbzUWaSKpWYsOk+V7mvkrMT1H\nLSUfLwcn+KWShvP3K7gdf4SVeE1bn4JuzJUqa0dzsnR6EOVEmcZ6jLs025hSeAchxJsALk+5vwPA\nbSn3vwLgK1Np80QgjoVc1viknnNUMBG4AREu6NXHXjHWVXEdXNinf9GBmPjbTEivi8XTKMZMJodR\nuYib6UFmrNE18JDOJvm3Qr3WZy4k4WrMVnVyeY5I4dvDA9fJ5zkq9WxRDgBUqzUoeYlXzO6vrc17\nL6aekVhRU5SfYnSK3NBS6S0AQN/AqLbZarWsJElan4BSTb+JdEKnGwv7Fz5n0oivlIWfyWgEYKI1\nW11WDxEDphNLwsPXlcfSVlv/0tvGrO87NIjf2vl5XPHNx6angwAax44BAIotG5tf1T+7xeW1szc9\nXRhbjojztzFNsJCVJ7w5NWGVOYYMxIOjqAlVUQosOX+l2+nBAqtW11t1KTSbQ9rfy8zU0Xez56hg\nMGKIykUmoT1YLrXtnpMuG1rAHNSqdf3mzU92upNbqT80Kjz0yy7jwgSUQlifJlQvjlVQoSdsiL96\n1m3LuVmopp4LAn41JP5eW89X2wZ2O/mU09D/2GHUnPOmp4MArn3up7jkpz/CirGjxrLt4yGxnDii\n5x4VXCf7CO1rrF04spLNpEK+bC6NZxYJGJdlUgQqjAyMWJUD9I5RVY08mUP10DY6IwA0a3Z97G/q\nCZfPdSKaDVqlzTRmqeshvAOkKaxjuVGUNM8z4M5qJT2hrXDfD826rK5dh58+cBJe/a5+/Qs5g4GG\nn9KGy2ZQUVZtiL+1clHVPUec/5KI6llZFcbxGG8fN5QM4RpekE3XX4Q9z4/j/Fs2T7lvCqVWG6fv\n/TlAaVa1SbSOhy/bxJieyzz7hZ14bt1poP5sQujqAmgx9GL50jrsAQ2gMJEt/+ZhG3yNZQdHX5/9\ncb9SzRa/NGvZVh0cvdjGKwSGEAYKfTX9BsQtaHQWSSoGvZn4qyvzWMTxEuADxSN2z7ui8UPg+oCC\n5gQDAIFfBGB+RwdHhnBsv81pMRxroAmnbkv8lW7MxrxUPWvbPcCzPMFPN5YE8T9j5Qps3PEczn15\nHHjf9sxyURJ1gwmZ4xZwzV2ZFrAnBMepABhDfXiFubDsp2khXvHoN3HZ9yZR+rWPZpbxArtjby8J\nbEiKrurDdrL1oGxH/IsaM8pOVDTxNJbV7drrxbZbweSFrFA2GADYQoXkMMWZ6sVXoTU+EX4WxqzK\nlzW6GJeHGUlJxs4RRlg1E//lQ2YGCYiForqwEqY+KQROD6ae8lNY6op8U3KHGcKSIP79zSpueGoE\nE65hYckwCDRhRxCnE5etOx9PvfwMLj3/XIvS8ghqYEIcARREC+VqNmemC6DFoWSeNov/SCUkHrU1\ng4aSIaolO/GV7YsKAI1qNoEfaDZw0RPPYOTt/cCl2ae3Qg+nHQXPso8mLtgWpUo4f61xQ+DAHkKS\nqI2+MWC3NioaWb6tKTEAeK7dhlgqlkGej9GNW7TlIjGuxoXctn81ucnaGDxEoiHLoTuWVnvTjSVB\n/PuqdQB7MT50QFuuNR7Knif22XEW04lVN2xE4zsVNDabZcaioDyW9eV8UcVxOo7TzlifWcYrVmDD\n2KpEHFYepZT8HxP6qvpN4t079+FwpQW61J6QVDUeoo2RUZy5+6/hG3IsoBcLGYmiIWb9dKMiRVjt\nST3xt43+CQCHK6HeqX6anfK6oVFe226GAOB79qa8n7zvT+FqQpADsbPhZDmbuNqGFqn2YGasrMPI\n0gltklZb1z2dWBIK37XDq7Dugw5u+9dXa8vZBvKaCbh9Afp//TSQZ5ZBrjwQ5osdHjusLfdPLr0I\nZ9fWY3RV9obiWyo/3XYoQz+8z7w5KbGZV7STrY+O6C1frj3UwKVP2ImQFMr1bJl/aWAQlReehv/C\nk9o6Yjd984531UA41qbF/NnigUd+iW99Xy966ZcxdgqTpj7ab2TqROlbiruqjex5LvWwGdpy/kC4\nbnVK4RDhWCuBxtrHUkzXMFgqJVqVJ6djk3reun4ofI/rnt0JebqxJDh/AHjPO99lLKOWgW+Sp8wx\nzvrVXvhPPIyT39ZP39qP3461hrpK5Rqg30MAAHUZnqI8ZrbMGagM4O0JoN482VwxgPqgXuxzw6e2\nYHKit+hXvsaWn3wfhZZ9DCXXIpjXfWeuxWvHxhNWTGm4pFnDjrctHjiAnW8UQDiCCzRlhob7gVeP\nYdwQLjnKaGEhh44izFoS7qpGed0L52+K998r1Dh0cZ58yzEOLFsJ/Pww/P3m8QSNcBPb7+gd/ja8\n/N8xvHcEWz96q7bcTGF+U7lZhiPpQc2189KcK/hOGc2jY3ALdiaSOpQ08Uw46qWQfCwbe9VYdmUl\ntMcfKNmJDUy+Bq7voFjpjfMPnKkrVFU8F0eYN4qgUMApmnjwCl/ffDJ2bd9k1X6bXLQM2a+GB8OT\n2FGDmiqyebfYyJSZqdNcpy237dmdOPWlnXAMcatsoUujeCJQG12xmc2123L+fiVkUKoV8xzX/FDn\nBUd/att+0Sb84PS/wcoVa636MN3IiT/DkYHwxfDOtZfvzQWqzjC2j29Af2H5lOsql+w2ukAS6Ork\nfmPZz56+CreM9uP8hp2360zA5Ln8jptvxXs++W+1ZaKMbXOkkBMFM6FeJufvqmUGohTZ7ptPUOcN\nhUT/zIFsXREAvFW9H4XxPzXWZwtbb3NbqKc3siZ7s/UtTyaOEkmNbDSW3VTYi8qBb+D8se9oy91x\n7h147JbHUO5B1zGdWDJiHxusHFqNnx88jnPXnzPXXdHiqNPCqe0VeLRgJsQmlDUpAjmoGHJPom6W\n+a8pBfjD081KLE8cwwTZWZTYwmkfRcviRHThjb9mLKNyzto6O003bv/sJWgbHID6PRdPXrgBywP9\nPLZk+HFqmYn/H56xDtftP4QNBl+EB27+cxxtmZ0SAWDw4OxnqxqaeAa7/QswWMwWK9py/lE5i9OJ\nWLYR5dc+g9K692nLFaiAum938p4J5MSfgcgDcBwlQ9KJucau0iE09k7ipeaRKddVtoyr469aBfxi\nP0rnXzjlNhX+dtsmjE+zcv1b55yCn429OS11FWTUVJojHVBQtpubVYaIsQAw2Q6V6uNvmDflPs/F\n9SOZ6bgjjFbtwm18t7EMXt/sP8MvbToX9zz5Bzi9eV9mGVudhPLfsCl91nBoPrx5uU5bM/fIiT/D\nDSNNPHZgDGsMbuhzjZO3VLHnRYGztvcW4CoNJUvirwKluYPTZ5lwpoGzPBFs6x/Ctn699ZAtlPXX\n+JG5E19NG6RjlCjPvhnzpi2z3yYAXDC6Dd96359pyziWnH8UTcui+JmDZ+LRmx/FQNFO5zVXyIk/\nw28sH8B1w32oTpMCa6Zw67tuxmPrH8PFKy6dcl01g620gsohIObADHau0O4LOdtDb9lZLc1nDFVH\ngfZRNMtTZxiWIiYjs187DJbmxnyzF+QK3w7Md8IPhMnJt6/cro35YouqpW21amrpkH7Aq4aij7Yh\nicxCgFMLT25DQwt/LHOBC/qquLhZxe+dYhF+ZYFgSpw/EfUD+AaAtQBeAXCzEOKtlHItAM/Krz8X\nQug1ITlmDWWnAAcCtwzpNz21zSwl4r+8vgw4cBANTXiMhYJlzRJw8CBOO8Usy19qOLNawpa6XgRZ\ndgp4YPMps9Sj2cFUxT53AnhECHEPEd0pv/+7lHJHhRDTFwIzx7TiF5earZsmojDNcxOBcC5Qa5aA\nAwex9sz5f4Q34Z+vGUbDdXDDyPwW+/zB+gH0WVqgTRce3nbarLY3XzBV4n8dgEvk9VcBfA/pxD/H\nAsdqaVEyajApXEwoKt+GYOGrxoJCAbevmh5F+EzigytXzXUXlgymuqpHhBB7AEAIsYeIsjJUFIlo\nB4BJAPcIIb41xXZzzDJuHGmi7jq4fGDhi0Bs8aHlg9hzfAIfW6VPvJIjx0KEkfgT0cMA0my17uqh\nndVCiN1EtA7A3xHRs0KIl1La+giAjwDA6tVzE+kuRzqICFcZYvAsNpScAu5eRAq+HDk4jMRfCJGZ\ntYSI9hLRqOT6RwH8KqOO3fLzZSL6HoBzAHQRfyHEvQDuBYCtW7cuJd1ijhw5cswqpmrq+W0AKiTd\nrQD+qrMAETWJKJDXgwDeCeAnU2w3R44cOXJMAVMl/vcAuJKIXgRwpfwOItpKRPfLMmcA2EFEzwB4\nFKHMPyf+OXLkyDGHmJLCVwjxJoDLU+7vAHCbvP5/AM6aSjs5cuTIkWN6kXv45siRI8cSRE78c+TI\nkWMJIif+OXLkyLEEkRP/HDly5FiCoPkaopeI3gBgThibjUEA+6apO3ONfCzzE/lY5i8W03h6Hcsa\nIYQxlse8Jf5TBRHtEEJsnet+TAfyscxP5GOZv1hM45mpseRinxw5cuRYgsiJf44cOXIsQSxm4n/v\nXHdgGpGPZX4iH8v8xWIaz4yMZdHK/HPkyJEjRzYWM+efI0eOHDkysOiIPxFdTUTPE9GtiNv5AAAE\nY0lEQVQumVpy3oOIXiGiZ4noaZn0BkTUT0QPEdGL8rMp7xMRfV6O78dEtGVuew8Q0ZeJ6FdEtJPd\n67n/RHSrLP8iEd2a1tYcjeVuIvqFnJ+niega9tu/l2N5nojeze7P+TokolVE9CgRPUdE/0hE/0Le\nX3BzoxnLgpsbIioS0RNE9Iwcy+/J+ycR0ePyGX+DiHx5P5Dfd8nf15rGaAUhxKL5A+AgzBOwDoAP\n4BkAG+a6Xxb9fgXAYMe93wdwp7y+E8Bn5PU1AP4WYU71CwA8Pg/6vx3AFgA7T7T/APoBvCw/m/K6\nOU/GcjeAT6WU3SDXWADgJLn2nPmyDgGMAtgir2sAXpB9XnBzoxnLgpsb+Xyr8toD8Lh83n8B4APy\n/h8D+Li8/gSAP5bXHwDwDd0Ybfux2Dj/8wDsEkK8LIQYB/B1hHmGFyKuQ5gXGfLzenb/ayLEDwH0\nUZhIZ84ghPg+gP0dt3vt/7sBPCSE2C+EeAvAQwCunvneJ5ExlixcB+DrQojjQoifAdiFcA3Oi3Uo\nhNgjhPiRvD4E4DkAK7AA50YzlizM27mRz3dMfvXknwBwGYAH5f3OeVHz9SCAy4mIkD1GKyw24r8C\nwGvs++vQL5D5AgHgu0T0DxSmsgQ68iMDUIlkF8oYe+3/fB/XJ6Uo5MtKTIIFNBYpKjgHIZe5oOem\nYyzAApwbInKI6GmE2Q8fQsi1HxBCTKb0K+qz/P0ggAFMcSyLjfhTyr2FYM70TiHEFgDvAfDbRLRd\nU3ahjlEhq//zeVx/BOBkAJsB7AHwOXl/QYyFiKoA/ieAO4QQb+uKptybV+NJGcuCnBshREsIsRnA\nSoTc+hlpxeTnjIxlsRH/1wGsYt9XAtg9R32xhohzHP8KwDcRLoa9SpxDyfzIC2WMvfZ/3o5LCLFX\nvqxtAPchPlrP+7EQkYeQWP6ZEOIv5e0FOTdpY1nIcwMAQogDAL6HUObfR0QqwRbvV9Rn+XsDoWhy\nSmNZbMT/SQDrpdbcR6gc+fYc90kLIqoQUU1dA7gKwE5k50f+NoAPScuMCwAcVEf4eYZe+/8dAFdR\nmPO5ifA5fGe2O52GDp3K+xHODxCO5QPSGuMkAOsBPIF5sg6lXPi/AXhOCPGf2E8Lbm6yxrIQ54aI\nhoioT16XAFyBUIfxKICbZLHOeVHzdROAvxOhxjdrjHaYTS33bPwhtFh4AaEM7a657o9Ff9ch1Ng/\nA+AfVZ8RyvQeAfCi/OwXsaXAF+X4ngWwdR6M4c8RHrknEHIjv3Ui/QfwzxAqrXYB+PA8GsufyL7+\nWL5wo6z8XXIszwN4z3xahwAuQigG+DGAp+XfNQtxbjRjWXBzA2ATgKdkn3cC+B15fx1C4r0LwAMA\nAnm/KL/vkr+vM43R5i/38M2RI0eOJYjFJvbJkSNHjhwWyIl/jhw5cixB5MQ/R44cOZYgcuKfI0eO\nHEsQOfHPkSNHjiWInPjnyJEjxxJETvxz5MiRYwkiJ/45cuTIsQTx/wEPw/EddsdNgQAAAABJRU5E\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ff7cfade10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ensemble error is 83.84019549936954% of best single ESN error\n"
     ]
    }
   ],
   "source": [
    "plt.plot(finalPrediction, label=\"prediction\")\n",
    "plt.plot(outputDataValidation, label=\"groundtrouth\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "for dat in singlePredictions:\n",
    "    plt.plot(dat)\n",
    "plt.show()\n",
    "\n",
    "#calculate error value\n",
    "judgeMSE = np.mean((finalPrediction - outputDataValidation)**2)\n",
    "#print(judgeMSE)\n",
    "\n",
    "#calculate best performing single error\n",
    "singlePredictions = np.array(singlePredictions)\n",
    "singleMSEs = []\n",
    "for i in range(len(singlePredictions)):\n",
    "    singleMSEs.append(np.mean((outputDataValidation - singlePredictions[i])**2))\n",
    "singleMSEs = np.array(singleMSEs)\n",
    "\n",
    "bestSingleMSE = np.min(singleMSEs)\n",
    "    \n",
    "#print(bestSingleMSE)\n",
    "\n",
    "print(\"Ensemble error is {0}% of best single ESN error\".format(100.0/bestSingleMSE*judgeMSE))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-17T15:48:33.034708Z",
     "start_time": "2018-02-17T15:48:33.030704Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-17T15:49:43.583507Z",
     "start_time": "2018-02-17T15:49:43.579513Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-17T15:49:51.771573Z",
     "start_time": "2018-02-17T15:49:51.768080Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-17T15:49:57.265261Z",
     "start_time": "2018-02-17T15:49:57.261770Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-17T15:50:15.550456Z",
     "start_time": "2018-02-17T15:50:15.546453Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-17T15:50:19.517389Z",
     "start_time": "2018-02-17T15:50:19.513886Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T08:41:00.577070Z",
     "start_time": "2018-02-18T08:41:00.570068Z"
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T08:43:48.883582Z",
     "start_time": "2018-02-18T08:43:48.880080Z"
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T09:59:10.617290Z",
     "start_time": "2018-02-18T09:59:10.612285Z"
    }
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:16:46.958493Z",
     "start_time": "2018-02-18T14:16:46.411521Z"
    }
   },
   "outputs": [],
   "source": [
    "trainErrors = []\n",
    "trainPredictions = []\n",
    "\n",
    "#TODO: get value for transientTimeValue\n",
    "transientTimeValue = 100\n",
    "\n",
    "ensembleSize = 10\n",
    "ensemble = []\n",
    "\n",
    "#train ensemble\n",
    "for _ in range(ensembleSize):\n",
    "    esn = PredictionESN(n_input=1, n_output=1, n_reservoir=50, leakingRate=0.2, regressionParameters=[1e-2], solver=\"lsqr\", feedback=False)\n",
    "    ensemble.append(esn)\n",
    "    error = esn.fit(inputDataTraining, outputDataTraining)\n",
    "    esn.resetState()\n",
    "    prediction = esn.predict(inputDataTraining)\n",
    "    trainPredictions.append(prediction)\n",
    "    trainErrors.append(error)\n",
    "\n",
    "\n",
    "judgeESNTrainData = np.array(trainPredictions)#.reshape(-1, len(trainPredictions))\n",
    "judgeESNTrainData = np.vstack((inputDataTraining.reshape((1, -1, 1)), judgeESNTrainData))\n",
    "judgeESNTrainData = judgeESNTrainData.T[0, transientTimeValue:]\n",
    "\n",
    "trainErrors = np.array(trainErrors)  \n",
    "weights = trainErrors / np.sum(trainErrors) * len(ensemble)\n",
    "\n",
    "judge = PredictionESN(n_input=1 + ensembleSize, n_output=1, n_reservoir=50, leakingRate=0.2, regressionParameters=[1e-2], solver=\"lsqr\", feedback=False)\n",
    "judge.fit(judgeESNTrainData, outputDataTraining[transientTimeValue:, ], transientTime=\"Auto\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:16:54.352684Z",
     "start_time": "2018-02-18T14:16:54.278114Z"
    }
   },
   "outputs": [],
   "source": [
    "#get predictions\n",
    "predictions = []\n",
    "for esn in ensemble:\n",
    "    prediction = esn.predict(inputDataValidation)\n",
    "    predictions.append(prediction)\n",
    "\n",
    "judgeESNInputData = np.array(predictions)\n",
    "judgeESNInputData = np.vstack((inputDataValidation.reshape(1, -1, 1), judgeESNInputData))\n",
    "judgeESNInputData = judgeESNInputData.T[0]\n",
    "\n",
    "finalPrediction = judge.predict(judgeESNInputData)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:16:55.629148Z",
     "start_time": "2018-02-18T14:16:55.454454Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYYAAAD8CAYAAABzTgP2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nlFKdaGJQSinVyf8HWnK5XVmsvPkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1eec28e84a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYYAAAD8CAYAAABzTgP2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1eec2942d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(finalPrediction)\n",
    "plt.show()\n",
    "\n",
    "for a in predictions:\n",
    "    plt.plot(a)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T14:14:37.373405Z",
     "start_time": "2018-02-18T14:14:37.369401Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-3.07110645e+00,  3.67497970e+00,  1.75495856e-01,\n",
       "         6.52550501e-03, -7.40927348e-02, -1.00456961e-01,\n",
       "        -9.49669496e-02, -7.15220737e-02, -3.82776906e-02,\n",
       "         2.84275918e-04,  4.19096462e-02,  8.55946417e-02,\n",
       "         6.32259295e-01, -3.34718571e-01, -6.36662989e-01,\n",
       "        -1.30688493e+00,  8.39671516e-01, -3.16391040e-01,\n",
       "         4.13176362e-01, -1.50605515e+00, -6.29995320e-01,\n",
       "         6.84388353e-01, -4.86265719e-03,  1.64239863e+00,\n",
       "        -7.84940454e-01, -2.38901397e-01, -5.95866106e-01,\n",
       "        -7.73475798e-01,  6.98809934e-01,  2.34469289e+00,\n",
       "         4.39528888e-02,  3.03168730e-01,  1.16971204e+00,\n",
       "        -1.32212480e+00,  6.39020433e-01,  2.29544087e+00,\n",
       "         1.82479845e-01, -4.67998502e-02, -2.18350753e+00,\n",
       "         3.92424128e-01, -1.08341352e+00,  3.27581510e-01,\n",
       "        -1.01137568e+00, -6.73759285e-01, -9.98251607e-01,\n",
       "        -5.02757951e-01,  2.47259528e-02,  2.46858099e-01,\n",
       "        -7.14414024e-02,  1.33537394e-01,  9.86361414e-01,\n",
       "         3.92822199e-01,  1.68599395e-01,  3.36333944e-02,\n",
       "        -4.15986174e-01,  3.75593468e+00,  1.30834635e+00,\n",
       "        -3.88388730e-02, -1.08207830e+00,  6.84085183e-01,\n",
       "        -5.39219341e-01,  2.98925519e-01]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "judge._WOut"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
